我有一个这种类型的file.dat，但有更多的数据：
Apr 1 18:15 [n1_Cam_A_120213_O.fits]:
4101.77 1. -3.5612 3.561 -0.278635 4.707 6.448 #data1
0.03223 0. 0.05278 0.05278 0.00237 0.4393 0.4125 #error1
4088.9 1. -0.404974 0.405 -0.06538 5.819 0. #data2
0. 0. 0.01559 0.01559 0.00277 0.1717 0. #error2
4116.4 1. -0.225521 0.2255 -0.041111 5.153 0. #data3
0. 0. 0.01947 0.01947 0.00368 0.4748 0. #error3
4120.8 1. -0.382279 0.3823 -0.062194 5.774 0. #data4
0. 0. 0.01873 0.01873 0.00311 0.3565 0. #error4
Apr 1 18:15 [n1_Cam_B_120213_O.fits]:
4101.767 0.9999 -4.57791 4.578 -0.388646 0.03091 7.499 #data1
0.0293 0. 0.03447 0.03447 0.00243 0.00873 0.07529 #error1
4088.9 1. -0.211493 0.2115 -0.080003 2.483 0.
0. 0. 0.01091 0.01091 0.00327 0.1275 0.
4116.4 1. -0.237161 0.2372 -0.040493 5.502 0.
0. 0. 0.02052 0.02052 0.00231 0.5069 0.
4120.8 1. -0.320798 0.3208 -0.108827 2.769 0.
0. 0. 0.0167 0.0167 0.00404 0.1165 0.
每个数据集的第一行包含name.fits，偶数行包含值，奇数行（第一行除外）包含之前行中值的错误。然后是一个空行并重新开始。
我需要的是以这种方式将信息分成不同的文件：
name1.fits data1[1] err1[1] data1[2] err1[2] data1[3] err1[3]...
name2.fits data1[1] err1[1] data1[2] err1[2] data1[3] err1[3]...
所以下一个文件是
name1.fits data2[1] err2[1] data2[2] err2[2] data2[3] err2[3]...
name2.fits data2[1] err2[1] data2[2] err2[2] data2[3] err2[3]...
然后我的数据的第一个新文件看起来像：
n1_Cam_A_120213_O.fits 4101.77 0.03223 1. 0. -3.5612 0.05278 3.561 0.05278 -0.278635 0.00237 4.707 0.4393 6.448 0.4125
n1_Cam_B_120213_O.fits 4101.767 0.0293 0.9999 0. -4.57791 0.03447 4.578 0.03447 -0.388646 0.00243 0.03091 0.00873 7.499 0.07529
这是我到目前为止所做的：
with open('file.dat','r') as data, open('names.txt', 'a') as nam, open('values.txt', 'a') as val, open('errors.txt', 'a') as err:
for lines in data.readlines():
cols = lines.split()
if "fits" in lines:
header = lines.split()
nam.write(header[3])
elif float(cols[0]) > 1:
#print cols[0]
x=str(cols)
val.write(x)
elif float(cols[0]) < 1:
#print cols[0]
y=str(cols)
err.write(y)
我刚开始使用python。我想到了不同文件中的单独名称值和错误，然后选择我需要的行和列。但由于我将处理数百个行和文件，我想要一种更自动的方法。我想要的是读取前3行并写入file1，然后是行1,4,5并写入file2，然后是行1,6,7并写入file3，然后是行1,8,9并写入file4，然后跳过空白行和读取行11,12,13，然后写入file1，然后是行11,14,15和写入文件2，依此类推（或类似的东西）。
答案 0 :(得分：0)
请尝试以下代码，这是您需要的吗？
结果命名方案为0,1,2，...
first = False
for i in open('file.dat'):
i = i.strip()
if not i:
continue
if 'fits' in i:
name = i.split()[3][1:-2]
data = None
first = not first
if first:
out = []
cur = -1
else:
if not data:
data = i.split()
if first:
out.append(open('%d' % len(out), 'w'))
else:
cur += 1
out[cur].write(name)
else:
for d, e in zip(data, i.split()):
out[cur].write(' %s %s' % (d, e))
out[cur].write('\n')
data = None
答案 1 :(得分：0)
我终于设法让它发挥作用，但也许你可以给我一些提示，让它变得更好。这是：
with open('file.log','r') as data, open('out1.txt', 'w') as out1, open('out2.txt', 'w') as out2:
def readError(error): # original data had errors inside parenthesis
newError = []
for e in error:
e = e.replace('(','').replace(')','')
e = e.split()
newError.extend(e)
return newError
for lines in open('file.log','r'):
lines = data.readline()
cols = lines.strip().split()
if "fits" in lines:
name = cols[3].replace('[','').replace(']','').replace(':','') + ' ' + '0' + ' ' + '1'
# 0 and 1 were some indexes I needed to add to each line
for i in range(0,2): # I needed to write 2 files
dato = data.readline().strip().split()
error_dato = readError(data.readline().strip().split())
newline = ''
if i == 0:
newline = name
for j in range(0, 7): # data had 7 columns
newline = newline + ' ' + dato[j] + ' ' + error_dato[j]
print newline
out1.write(newline + '\n')
elif i == 1:
newline = name
for j in range(0, 7):
newline = newline + ' ' + dato[j] + ' ' + error_dato[j]
print newline
out2.write(newline + '\n')
linea = data.readline().strip()
# I don't know why the code doesn't work without this line