NumPy Генерирует ValueError: Обнаружены некоторые ошибки!Строка № 9 (получено 42 столбца вместо 1) - PullRequest
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NumPy Генерирует ValueError: Обнаружены некоторые ошибки!Строка № 9 (получено 42 столбца вместо 1)

0 голосов
/ 26 сентября 2019

Я пишу код для объединения текстовых файлов, и я столкнулся с ошибкой, которую мне не удается решить.Google не помогает.

Код: 

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 26 09:51:55 2019

@author: comp
"""
import numpy as np

NAME = input("Enter Molecule ID: ")
NAME_IN = NAME+'_apo-1acl.RMSD'

DATA = []
DATA = np.genfromtxt(NAME_IN, skip_header=7, dtype=None, delimiter=' ')

Текстовый файл: 

    RMSD TABLE
    __________

_____________________________________________________________________
     |      |      |           |         |                 |
Rank | Sub- | Run  | Binding   | Cluster | Reference       | Grep
     | Rank |      | Energy    | RMSD    | RMSD            | Pattern
_____|______|______|___________|_________|_________________|___________
   1      1      8       -7.23      0.00     93.07           RANKING
   1      2      9       -6.79      1.39     92.64           RANKING
   2      1     16       -7.18      0.00     93.19           RANKING
   3      1      2       -6.93      0.00     93.38           RANKING
   3      2     17       -6.84      0.23     93.45           RANKING
   4      1     15       -6.55      0.00     91.83           RANKING
   4      2      7       -6.34      0.33     91.77           RANKING
   5      1      5       -6.41      0.00     93.05           RANKING
   6      1      3       -6.36      0.00     92.84           RANKING
   6      2     10       -6.28      0.47     92.92           RANKING
   6      3      6       -6.27      0.43     92.82           RANKING
   6      4     18       -6.25      0.32     92.88           RANKING
   6      5     13       -6.24      0.96     92.75           RANKING
   6      6      1       -6.24      0.87     92.60           RANKING
   6      7     14       -6.21      0.51     92.90           RANKING
   6      8     11       -6.14      0.98     92.78           RANKING
   6      9     20       -6.11      0.71     92.67           RANKING
   6     10     19       -6.01      1.36     93.00           RANKING
   7      1     12       -6.30      0.00     93.28           RANKING
   8      1      4       -5.85      0.00     92.97           RANKING
_______________________________________________________________________

и ошибка: 

Traceback (most recent call last):

  File "/home/comp/Apps/Models/1-PhosphorusLigands/CombinedLigands/MOL/Docking/Results/RMSDTable/CombineRMSDFiles.py", line 14, in <module>
    DATA = np.genfromtxt(NAME_IN, skip_header=7, dtype=None, delimiter=' ')

  File "/home/comp/Apps/Miniconda3/lib/python3.7/site-packages/numpy/lib/npyio.py", line 2075, in genfromtxt
    raise ValueError(errmsg)

ValueError: Some errors were detected !
    Line #9 (got 42 columns instead of 1)
    Line #10 (got 42 columns instead of 1)
    Line #11 (got 41 columns instead of 1)
    Line #12 (got 42 columns instead of 1)
    Line #13 (got 41 columns instead of 1)
    Line #14 (got 41 columns instead of 1)
    Line #15 (got 42 columns instead of 1)
    Line #16 (got 42 columns instead of 1)
    Line #17 (got 42 columns instead of 1)
    Line #18 (got 41 columns instead of 1)
    Line #19 (got 42 columns instead of 1)
    Line #20 (got 41 columns instead of 1)
    Line #21 (got 41 columns instead of 1)
    Line #22 (got 42 columns instead of 1)
    Line #23 (got 41 columns instead of 1)
    Line #24 (got 41 columns instead of 1)
    Line #25 (got 41 columns instead of 1)
    Line #26 (got 40 columns instead of 1)
    Line #27 (got 41 columns instead of 1)
    Line #28 (got 42 columns instead of 1)

На данный момент я даже не знаю, как задать вопрос.

1 Ответ

0 голосов
/ 26 сентября 2019

С помощью copy-n-paste образца вашего файла: 

In [89]: np.genfromtxt(txt.splitlines(), dtype=None, encoding=None, skip_header=
    ...: 8)                                                                     
Out[89]: 
array([(1,  1,  8, -7.23, 0.  , 93.07, 'RANKING'),
       (1,  2,  9, -6.79, 1.39, 92.64, 'RANKING'),
       (2,  1, 16, -7.18, 0.  , 93.19, 'RANKING'),
       (3,  1,  2, -6.93, 0.  , 93.38, 'RANKING'),
       (3,  2, 17, -6.84, 0.23, 93.45, 'RANKING'),
       (4,  1, 15, -6.55, 0.  , 91.83, 'RANKING'),
       (4,  2,  7, -6.34, 0.33, 91.77, 'RANKING'),
       (5,  1,  5, -6.41, 0.  , 93.05, 'RANKING'),
       (6,  1,  3, -6.36, 0.  , 92.84, 'RANKING'),
       (6,  2, 10, -6.28, 0.47, 92.92, 'RANKING'),
       (6,  3,  6, -6.27, 0.43, 92.82, 'RANKING'),
       (6,  4, 18, -6.25, 0.32, 92.88, 'RANKING'),
       (6,  5, 13, -6.24, 0.96, 92.75, 'RANKING'),
       (6,  6,  1, -6.24, 0.87, 92.6 , 'RANKING'),
       (6,  7, 14, -6.21, 0.51, 92.9 , 'RANKING'),
       (6,  8, 11, -6.14, 0.98, 92.78, 'RANKING'),
       (6,  9, 20, -6.11, 0.71, 92.67, 'RANKING'),
       (6, 10, 19, -6.01, 1.36, 93.  , 'RANKING'),
       (7,  1, 12, -6.3 , 0.  , 93.28, 'RANKING'),
       (8,  1,  4, -5.85, 0.  , 92.97, 'RANKING')],
      dtype=[('f0', '<i8'), ('f1', '<i8'), ('f2', '<i8'), ('f3', '<f8'), ('f4', '<f8'), ('f5', '<f8'), ('f6', '<U7')])
...