我有一个文件CASE.dat文件
# X Y Z TARGET MY DIST MY DATA
--------------------------------------------------------------------------------
1 16.136051 19.214215 26.195842 0.935901 0.528294 10305.052469
2 19.296614 20.459830 20.711839 4.033354 1.152114 258.468669
3 21.757247 20.010601 21.609096 4.008830 1.117961 208.482335
4 23.340579 20.230572 20.299311 0.962172 0.567720 1648.046276
5 22.232850 19.276643 24.105109 4.028086 1.105535 116.818198
6 20.177439 18.995924 25.744873 4.020979 1.119227 259.240957
7 20.507640 18.422719 27.698151 0.973875 0.578381 4433.058006
8 17.718280 19.441795 24.896309 4.052598 1.117063 399.224573
9 17.274647 20.170761 22.411821 4.049756 1.067280 369.719958
10 15.344147 20.532170 21.791338 0.942252 0.522218 2903.487129
11 16.747362 21.490591 16.828061 4.119692 1.052854 640.628897
12 18.942734 21.191117 18.059497 4.016967 1.013168 370.875172
13 16.713317 22.043861 14.846116 0.952206 0.572128 15824.211118
14 14.917097 21.194983 17.726730 0.996560 0.573948 8439.378683
15 20.697846 21.496657 17.007974 0.931434 0.494488 4811.530560
16 24.891192 18.784856 25.017254 4.004345 1.086042 87.628933
17 24.849590 17.270757 26.442292 0.986123 0.548764 2084.437203
18 26.020588 18.043376 23.429171 0.962405 0.489209 5797.201598
19 29.699839 22.572565 28.810307 4.025628 1.079363 339.526719
20 31.243469 22.179022 30.120360 0.974974 0.569833 5998.952157
21 29.172195 25.093904 28.162412 3.991001 1.124966 301.999963
我的目标是对第5列进行一些处理。
我使用以下脚本提取它
cat CASE.dat | awk '{print $5}' | awk NF | awk 'NR>1'
这给了我
0.935901
4.033354
4.008830
0.962172
4.028086
4.020979
0.973875
4.052598
4.049756
0.942252
4.119692
4.016967
0.952206
0.996560
0.931434
4.004345
0.986123
0.962405
4.025628
0.974974
3.991001
现在我需要一个可以改进我上面的脚本的建议。此外，我这里有两种类型的数字，一种是~4，另一种是~1。我想把2.0加到所有的是~4的数字中，把1.0加到所有的~1的数字中。请提出任何简单的答案。
直到这个结果应该是
1.935901
6.033354
6.008830
1.962172
6.028086
6.020979
1.973875
6.052598
6.049756
1.942252
6.119692
6.016967
1.952206
1.996560
1.931434
6.004345
1.986123
1.962405
6.025628
1.974974
5.991001
最后，我想从6中减去~6(这个数字在另一个文件中可能不同(，从2中减去~1(这个数字可能在另一文件中不同(。最终数据应为
0.064099
-0.033354
-0.00883
0.037828
-0.028086
-0.020979
0.026125
-0.052598
-0.049756
0.057748
-0.119692
-0.016967
0.047794
0.00344
0.068566
-0.004345
0.013877
0.037595
-0.025628
0.025026
0.008999
您可以使用此awk:
awk -v d='0.009' 'NR <= 2 {next} {n = int($5+d)} n == 4 {$5 += 2} n == 1 {$5 += 1} {n = int($5+d)} n==6 || n==1 {$5 = n - $5} {print $5}' case.dat
0.935901
-0.033354
-0.00883
0.962172
-0.028086
-0.020979
0.973875
-0.052598
-0.049756
0.942252
-0.119692
-0.016967
0.952206
1.99656
0.931434
-0.004345
0.986123
0.962405
-0.025628
0.974974
0.008999
更可读的格式：
awk -v d='0.009' 'NR <= 2 { next }
{n = int($5+d)}
n == 4 {$5 += 2}
n == 1 {$5 += 1}
{n = int($5+d)}
n == 6 || n == 1 {
$5 = n - $5
}
{print $5}' case.dat
开始：
import math
import numpy as np
with open("CASE.dat", "r") as msg:
data = msg.readlines()
for i, line in enumerate(data[2:]):
row = list(map(float, line.strip().split()))
if round(row[4]) == 1:
val = 1
elif round(row[4]) == 4:
val = 2
row[4] = row[4] + val
if round(row[4]) == 6:
row[4] = 6 - row[4]
elif round(row[4]) == 2:
row[4] = np.abs(row[4] - 2)
data[i+2] = " ".join(map(str,row))
for row in data:
print (row)
你得到：
# X Y Z TARGET MY DIST MY DATA
--------------------------------------------------------------------------------
1.0 16.136051 19.214215 26.195842 0.06409900000000013 0.528294 10305.052469
2.0 19.296614 20.45983 20.711839 -0.033354000000000106 1.152114 258.468669
3.0 21.757247 20.010601 21.609096 -0.008829999999999671 1.117961 208.482335
4.0 23.340579 20.230572 20.299311 0.03782799999999997 0.56772 1648.046276
5.0 22.23285 19.276643 24.105109 -0.028086000000000055 1.105535 116.818198
6.0 20.177439 18.995924 25.744873 -0.020978999999999637 1.119227 259.240957
7.0 20.50764 18.422719 27.698151 0.026124999999999954 0.578381 4433.058006
8.0 17.71828 19.441795 24.896309 -0.0525979999999997 1.117063 399.224573
9.0 17.274647 20.170761 22.411821 -0.049756000000000355 1.06728 369.719958
10.0 15.344147 20.53217 21.791338 0.05774800000000013 0.522218 2903.487129
11.0 16.747362 21.490591 16.828061 -0.11969199999999969 1.052854 640.628897
12.0 18.942734 21.191117 18.059497 -0.016967000000000176 1.013168 370.875172
13.0 16.713317 22.043861 14.846116 0.047794000000000114 0.572128 15824.211118
14.0 14.917097 21.194983 17.72673 0.0034399999999998876 0.573948 8439.378683
15.0 20.697846 21.496657 17.007974 0.06856600000000013 0.494488 4811.53056
16.0 24.891192 18.784856 25.017254 -0.004344999999999821 1.086042 87.628933
17.0 24.84959 17.270757 26.442292 0.013876999999999917 0.548764 2084.437203
18.0 26.020588 18.043376 23.429171 0.037595000000000045 0.489209 5797.201598
19.0 29.699839 22.572565 28.810307 -0.025628000000000206 1.079363 339.526719
20.0 31.243469 22.179022 30.12036 0.025025999999999993 0.569833 5998.952157
21.0 29.172195 25.093904 28.162412 0.008999000000000201 1.124966 301.999963