biopython 1.78 MarkovModel.train_visibletraining_data是什么类型？

问题描述

我想使用biopython的Bio.MarkovModel.train_visible（）为核苷酸序列训练二阶Markov模型。也就是说，alphabet=["A","T","G","C"],states=["AA","AT","TT"...]

但是，我得到一个错误：

    474     states_indexes = itemindex(states)
    475     outputs_indexes = itemindex(alphabet)
--> 476     for toutputs,tstates in training_data:
    477         if len(tstates) != len(toutputs):
    478             raise ValueError("states and outputs not aligned")
 ValueError: too many values to unpack (expected 2)

表明我可能会给 我尝试将我的training_data作为一对列表提供：

training_data=(['A','T'...],['AA','AT'...])

以及此列表对的压缩列表：

training_data=[('A','AA'),('T','AT')...]

但无济于事。 training_set的正确格式是什么？ 谢谢！

解决方法

有关预期输入的示例，请参见文件test_MarkovModel.py：

>>> from Bio import MarkovModel

>>> states = ["0","1","2","3"]
>>> alphabet = ["A","C","G","T"]
>>> training_data = [
            ("AACCCGGGTTTTTTT","001112223333333"),("ACCGTTTTTTT","01123333333"),("ACGGGTTTTTT","01222333333"),("ACCGTTTTTTTT","011233333333"),]
>>> markov_model = MarkovModel.train_visible(states,alphabet,training_data)
>>> states = MarkovModel.find_states(markov_model,"AACGTT")
>>> print(states)
[(['0','0','1','2','3','3'],0.008212890625000005)]