I have a large file that has a lot of timing information. An excerpt looks like CPU time for df vj and vk 329.45135 sec, wall time 10.42650 sec CPU time for df vj and vk 331.06361 sec, wall time 10.48211 sec CPU time for df vj and vk 330.34512 sec, wall time 10.45198 sec CPU time for df vj and vk 330.43818 sec, wall time 10.46212 sec CPU time for orbital rotation 1341.99499 sec, wall time 42.54674 sec CPU time for update CAS DM 12.02945 sec, wall time 0.37361 sec CPU time for micro iter 1 0.00003 sec, wall time 0.00003 sec CPU time for density fitting ao2mo pass1 157.41450 sec, wall time 19.02017 sec CPU time for density fitting papa pass2 11.19426 sec, wall time 0.61816 sec CPU time for density fitting ppaa pass2 24.55801 sec, wall time 6.68668 sec CPU time for df vj and vk 171.32896 sec, wall time 5.41600 sec CPU time for density fitting ao2mo 366.81797 sec, wall time 33.65705 sec CPU time for update eri 366.82145 sec, wall time 33.66198 sec CPU time for integral transformation to CAS space 0.00001 sec, wall time 0.00000 sec I have to calculate sum of all df vj and vk and density fitting ao2mo , among several other parameters. My core functionality is total+=sum([float(line.split()[position]) for line in open(file_name).readlines() if parameter in line]) where position depends on whether I am trying to get CPU time or wall time, file_name is file in which text is stored, and parameter is the function I am trying to collect data for. I get 47.23871 for df vj and vk and 33.65705 for density fitting ao2mo . The question is as follows - density fitting ao2mo contains the time of df vkj and vk above it (the 5.41600 sec line). I would like df vj and vk to exclude the lines where it is immediately followed by line containing density fitting ao2mo . Therefore, I would like the result to be df vj and vk as 41.82271. How can I do this? Continue reading...
