Question

我在scikit-tensor中使用以下代码进行parafac分解。此代码是scikit-tensor的示例。

from sktensor import dtensor, cp_als, parafac2, tucker_hooi
import numpy
import sktensor

T=dtensor(numpy.arange(100).reshape(2, 5,10))
print (type(T))

P, F, D, A, fit, itr, exectimes = parafac2.parafac2(T, 3, init=3, ma_iter=5, conv= 4)

当我运行此代码时，输出为......

Traceback (most recent call last):
  File "C:/Users/meghdad/PycharmProjects/tensorInPython/dtensor1.py", line 17, in <module>
    P, F, D, A, fit, itr, exectimes = parafac2.parafac2(T, 3, init=3, ma_iter=5, conv= 4)
  File "C:\Anaconda3\lib\site-packages\scikit_tensor-0.1-py3.5.egg\sktensor\parafac2.py", line 50, in parafac2
  File "C:\Anaconda3\lib\site-packages\scikit_tensor-0.1-py3.5.egg\sktensor\parafac2.py", line 113, in __init
UnboundLocalError: local variable 'F' referenced before assignment

如何解决此错误？

Answer 1

我查看版本0.1的source code。＆＃34; init＆＃34;的唯一有效值关键字是＆＃34; nvecs＆＃34;或＆＃34;随机＆＃34;。默认值为＆＃34; nvecs＆＃34;。如果您尝试其中任何一种，您将摆脱错误：

P, F, D, A, fit, itr, exectimes = parafac2.parafac2(T, 3, init='nvecs', ma_iter=5, conv= 4)

或者

P, F, D, A, fit, itr, exectimes = parafac2.parafac2(T, 3, init='random', ma_iter=5, conv= 4)

使用scikit-tensor进行张量分析

1 个答案: