Question

我有一个n x n numpy float64 sparse matrix（data，其中n = 44），其中行和列是图节点，这些值是边缘权重：

>>> data
<44x44 sparse matrix of type '<class 'numpy.float64'>'
    with 668 stored elements in Compressed Sparse Row format>

>>> type(data)
<class 'scipy.sparse.csr.csr_matrix'>

>>> print(data)
  (0, 7)    0.11793236293516568
  (0, 9)    0.10992000939300195
  (0, 21)   0.7422196678913772
  (0, 23)   0.0630039712667936
  (0, 24)   0.027037442463504143
  (0, 27)   0.16908845414214152
  (0, 28)   0.6109227233402952
  (0, 32)   0.0514765253537568
  (0, 33)   0.016341754080557713
  (1, 6)    0.015070325434709386
  (1, 10)   9.346673769086203e-05
  (1, 11)   0.2471018034781923
  (1, 14)   0.0020684269551621776
  (1, 18)   0.015258704502643251
  (1, 20)   0.021798149289490358
  (1, 22)   0.0087026831764125
  (1, 24)   0.1454235884185166
  (1, 25)   0.022060777594183015
  (1, 29)   0.9117391202819067
  (1, 30)   0.018557883854566116
  (1, 31)   0.001876070225734826
  (1, 32)   0.025841354399637764
  (1, 33)   0.014766488228364438
  (1, 39)   0.002791226433410351
  (1, 43)   1.0
  : :
  (41, 7)   0.8922099840113696
  (41, 10)  0.015776226631920767
  (41, 12)  1.0
  (41, 15)  0.1839408706622038
  (41, 18)  0.5151025641025642
  (41, 20)  0.4599130036630037
  (41, 22)  0.29378473237788827
  (41, 33)  0.47474890700697153
  (41, 39)  1.0
  (42, 2)   1.0
  (42, 10)  0.023305789342610222
  (42, 11)  0.011349136164776494
  (42, 12)  1.0
  (42, 17)  0.886081346522542
  (42, 18)  1.0
  (42, 30)  1.0
  (42, 40)  1.0
  (43, 1)   1.0
  (43, 6)   1.0
  (43, 11)  0.039948959300013256
  (43, 13)  1.0
  (43, 14)  0.02669811947637717
  (43, 29)  1.0
  (43, 30)  1.0
  (43, 36)  0.3381986531986532

我想将其转换为pandas data frame，以便将其写入文件，其列为：node1, node2, edge_weight，因此将给出：

node1, node2, edge_weight
0, 7, 0.11793236293516568
0, 9, 0.10992000939300195
:, :, :
43, 36, 0.3381986531986532

有什么想法吗？

请注意：

>>> pandas.DataFrame(data)

给予：

                                                    0
0     (0, 7)\t0.11793236293516568\n  (0, 9)\t0.109...
1     (0, 6)\t0.015070325434709386\n  (0, 10)\t9.3...

和

>>> pandas.DataFrame(print(data))

礼物：

  (0, 7)    0.11793236293516568
  (0, 9)    0.10992000939300195

所以我想pandas.DataFrame(print(data))与我要寻找的东西很接近。

Answer 1

此ipython会话显示了一种实现方法。这两个步骤是：将稀疏矩阵转换为COO格式，然后使用COO矩阵的class TotoType extends AbstractType { public function buildForm(FormBuilderInterface $builder, array $options) { $builder ->add('name', TextType::class, [ 'help' => 'go tho the <a href="prenom.com">list</a> name' ]) ; } }，.row和.col属性创建Pandas DataFrame。

.data

Answer 2

您可以尝试<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script> <div id="blueBox" class="box"></div> <div id="redBox" class="box"></div> <div id="curURL"></div>

toarray

将numpy float64稀疏矩阵转换为熊猫数据框

2 个答案: