Python:如何从文本文件中提取字符串以用作数据

Question

这是我第一次编写 Python 脚本，开始时遇到了一些困难。假设我有一个名为 Test.txt 的 txt 文件，其中包含此信息。

                                   x          y          z      Type of atom
ATOM   1     C1  GLN D  10      26.395      3.904      4.923    C
ATOM   2     O1  GLN D  10      26.431      2.638      5.002    O
ATOM   3     O2  GLN D  10      26.085      4.471      3.796    O 
ATOM   4     C2  GLN D  10      26.642      4.743      6.148    C  

我想做的是最终编写一个脚本来找到这三个原子的质心。所以基本上我想总结那个 txt 文件中的所有 x 值，每个数字乘以一个给定的值，具体取决于原子的类型。

我知道我需要为每个 x 值定义位置，但我无法弄清楚如何使这些 x 值表示为数字而不是字符串中的 txt。我必须记住，我需要将这些数字乘以原子类型，因此我需要一种方法来为每种原子类型定义它们。谁能把我推向正确的方向？

Answer 1

mass_dictionary = {'C':12.0107,
                   'O':15.999
                   #Others...?
                  }

# If your files are this structured, you can just
# hardcode some column assumptions.
coords_idxs = [6,7,8]
type_idx = 9

# Open file, get lines, close file.
# Probably prudent to add try-except here for bad file names.
f_open = open("Test.txt",'r')
lines = f_open.readlines()
f_open.close()

# Initialize an array to hold needed intermediate data.
output_coms = []; total_mass = 0.0;

# Loop through the lines of the file.
for line in lines:

    # Split the line on white space.
    line_stuff = line.split()

    # If the line is empty or fails to start with 'ATOM', skip it.
    if (not line_stuff) or (not line_stuff[0]=='ATOM'):
        pass

    # Otherwise, append the mass-weighted coordinates to a list and increment total mass.
    else:
        output_coms.append([mass_dictionary[line_stuff[type_idx]]*float(line_stuff[i]) for i in coords_idxs])
        total_mass = total_mass + mass_dictionary[line_stuff[type_idx]]

# After getting all the data, finish off the averages.
avg_x, avg_y, avg_z = tuple(map( lambda x: (1.0/total_mass)*sum(x), [[elem[i] for elem in output_coms] for i in [0,1,2]]))


# A lot of this will be better with NumPy arrays if you'll be using this often or on
# larger files. Python Pandas might be an even better option if you want to just
# store the file data and play with it in Python.