Question

我正在尝试使用以下结构解析文本文件：

latitude                        5.0000
number_of_data_values             9
  0.1   0.2   0.3   0.4
  1.1   1.2   1.3   1.4      
  8.1
latitude                        4.3000
number_of_data_values             9
  0.1   0.2   0.3   0.4
  1.1   1.2   1.3   1.4       
  8.1
latitude                        4.0000
number_of_data_values             9
  0.1   0.2   0.3   0.4
  1.1   1.2   1.3   1.4       
  8.1
 ...

每个不同的latitude数字是不同的数组行。 number_of_data_values是colomns的数量（文件一致）。

对于这个例子，我想读取文件并输出一个3乘9的二维数组，如下所示：

array = [[0.1,0.2,0.3,0.4,1.1,1.2,1.3,1.4,8.1],
         [0.1,0.2,0.3,0.4,1.1,1.2,1.3,1.4,8.1],
         [0.1,0.2,0.3,0.4,1.1,1.2,1.3,1.4,8.1]]

我通过循环遍历循环来尝试它，但我正在寻找一种更有效的方法，因为我可以处理大量的输入文件。

Answer 1

似乎非常直截了当。解析数字的部分只是line.split()。其余的或解析可以加强或软化，具体取决于输入数据格式的稳定性。

results = []
latitude = None
numbers_total = None
value_list = []

for line in text.splitlines():
  if line.startswith('latitude '):
    if latitude is not None:
      assert len(value_list) == numbers_total
      results.append((latitude, value_list))
      value_list = []
    latitude = line.split()[-1]
  elif line.startswith('number_of_data_values '):
    numbers_total = int(line.split()[-1])
  else:
    value_list.extend(line.split())

# Make sure the last block gets added to the results.
if latitude is not None:
  assert len(value_list) == numbers_total
  results.append((latitude, value_list))
  value_list = []

for latitude, value_list in results:
  print 'latitude %r: %r' % (latitude, value_list)

输出：

latitude '5.0000': ['0.1', '0.2', '0.3', '0.4', '1.1', '1.2', '1.3', '1.4', '8.1']
latitude '4.3000': ['0.1', '0.2', '0.3', '0.4', '1.1', '1.2', '1.3', '1.4', '8.1']
latitude '4.0000': ['0.1', '0.2', '0.3', '0.4', '1.1', '1.2', '1.3', '1.4', '8.1']

Answer 2

逐行实现相当容易理解。假设你的latitude总是从一个新行开始（这不是你的例子给出的，但它可能是一个错字），你可以这样做：

latitudes = []
counts = []
blocks = []
current_block = []
for line in test:
    print line
    if line.startswith("latitude"):
        # New block: add the previous one to `blocks` and reset
        blocks.append(current_block)
        current_block = []
        latitudes.append(float(line.split()[-1]))
    elif line.startswith("number_of_data"):
        # Just append the current count to the list
        counts.append(int(line.split()[-1]))
    else:
        # Update the current block
        current_block += [float(f) for f in line.strip().split()]
# Make sure to add the last block...
blocks.append(current_block)
# And to remove the first (empty) one
blocks.pop(0)

您可以知道检查所有块是否具有适当的大小：

all(len(b)==c for (c,b) in zip(counts,blocks))

替代解决方案

如果您担心循环，可能需要考虑查询文件的内存映射版本。我们的想法是找到以latitude开头的行的位置。找到一个后，找到下一个，然后你有一个文本块：删除前两行（以latitude开头的那一行和以number_of_data开头的那一行），合并其余的行和处理。

import mmap

with open("crap.txt", "r+b") as f:
    # Create the mapper
    mapper = mmap.mmap(f.fileno(), 0)
    # Initialize your output variables
    latitudes = []
    blocks = [] 
    # Find the beginning of the first block
    position = mapper.find("latitude")
    # `position` will be -1 if we can't find it
    while (position >= 0):
        # Move to the beginning of the block
        mapper.seek(position)
        # Read the first line
        lat_line = mapper.readline().strip()
        latitudes.append(lat_line.split()[-1])
        # Read the second one
        zap = mapper.readline()
        # Where are we ?
        start = mapper.tell()
        # Where's the next block ?
        position = mapper.find("latitude")
        # Read the lines and combine them into a large string
        current_block = mapper.read(position-start).replace("\n", " ")
        # Transform the string into a list of floats and update the block
        blocks.append(list(float(i) for i in current_block.split() if i))

如何在Python中将块数据从文本文件解析为2D数组？

2 个答案: