INFO 2020-02-11 01:45:50,646Z lrauvNc4ToNetcdf.py processResampleNc4File():979 Reading /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 file... INFO 2020-02-11 01:45:50,647Z lrauvNc4ToNetcdf.py processResampleNc4File():980 After copying to /tmp/202002061308_202002061642.nc4 INFO 2020-02-11 01:45:51,687Z lrauvNc4ToNetcdf.py processResampleNc4File():982 Read file /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 INFO 2020-02-11 01:45:51,714Z lrauvNc4ToNetcdf.py createSeries():225 latitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:51,724Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:51,732Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable latitude INFO 2020-02-11 01:45:52,131Z lrauvNc4ToNetcdf.py createSeries():225 longitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:52,139Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:52,147Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable longitude INFO 2020-02-11 01:45:52,550Z lrauvNc4ToNetcdf.py createSeries():225 depth: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:52,561Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:52,572Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable depth INFO 2020-02-11 01:45:52,972Z lrauvNc4ToNetcdf.py createSeries():225 time: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:52,982Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:52,991Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable time INFO 2020-02-11 01:45:53,394Z lrauvNc4ToNetcdf.py createSeries():225 latitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:53,403Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:53,412Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable latitude INFO 2020-02-11 01:45:53,809Z lrauvNc4ToNetcdf.py createSeries():225 longitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:53,819Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:53,827Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable longitude INFO 2020-02-11 01:45:54,225Z lrauvNc4ToNetcdf.py createSeries():225 depth: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:54,235Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:54,245Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable depth INFO 2020-02-11 01:45:54,658Z lrauvNc4ToNetcdf.py createSeries():225 time: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:54,669Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:54,679Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable time INFO 2020-02-11 01:45:55,080Z lrauvNc4ToNetcdf.py createSeries():225 latitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:55,089Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:55,096Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable latitude INFO 2020-02-11 01:45:55,505Z lrauvNc4ToNetcdf.py createSeries():225 longitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:55,514Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:55,522Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable longitude INFO 2020-02-11 01:45:55,918Z lrauvNc4ToNetcdf.py createSeries():225 depth: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:55,927Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:55,934Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable depth INFO 2020-02-11 01:45:56,337Z lrauvNc4ToNetcdf.py createSeries():225 time: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:56,356Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:56,364Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable time INFO 2020-02-11 01:45:56,763Z lrauvNc4ToNetcdf.py createSeries():225 latitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:56,771Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:56,780Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable latitude INFO 2020-02-11 01:45:57,182Z lrauvNc4ToNetcdf.py createSeries():225 longitude: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:57,194Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:57,205Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable longitude INFO 2020-02-11 01:45:57,623Z lrauvNc4ToNetcdf.py createSeries():225 depth: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:57,636Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:57,650Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable depth INFO 2020-02-11 01:45:58,062Z lrauvNc4ToNetcdf.py createSeries():225 time: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695 31696] INFO 2020-02-11 01:45:58,071Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:58,078Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable time INFO 2020-02-11 01:45:58,466Z lrauvNc4ToNetcdf.py processResampleNc4File():987 Creating t variable of the time indexes WARNING 2020-02-11 01:45:58,479Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'mass_concentration_of_oxygen_in_sea_water' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:58,479Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'sea_water_salinity' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:58,479Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'sea_water_temperature' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:58,479Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'sea_water_salinity' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:58,480Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'sea_water_temperature' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:58,480Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'mole_concentration_of_nitrate_in_sea_water' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 INFO 2020-02-11 01:45:58,487Z lrauvNc4ToNetcdf.py createSeries():225 downwelling_photosynthetic_photon_flux_in_sea_water: v_t values found before 2020-02-06 13:08:00 and after 2020-02-06 16:42:00: [31667 31668 31669 31670 31671 31672 31673 31674 31675 31676 31677 31678 31679 31680 31681 31682 31683 31684 31685 31686 31687 31688 31689 31690 31691 31692 31693 31694 31695] INFO 2020-02-11 01:45:58,488Z lrauvNc4ToNetcdf.py createSeries():226 Their times: ['Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:00 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:01 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:02 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:03 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:04 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:05 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:06 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:07 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:08 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:09 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:10 2020', 'Thu Feb 6 16:42:11 2020', 'Thu Feb 6 16:42:11 2020'] INFO 2020-02-11 01:45:58,490Z lrauvNc4ToNetcdf.py createSeries():227 Removing them: [1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100732e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09 1.58100733e+09] for variable downwelling_photosynthetic_photon_flux_in_sea_water INFO 2020-02-11 01:45:59,050Z lrauvNc4ToNetcdf.py processResampleNc4File():1062 Found in group PAR_Licor parameter downwelling_photosynthetic_photon_flux_in_sea_water renaming to PAR WARNING 2020-02-11 01:45:59,050Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'mass_concentration_of_chlorophyll_in_sea_water' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:59,051Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'Output470' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 WARNING 2020-02-11 01:45:59,051Z lrauvNc4ToNetcdf.py processResampleNc4File():1064 'Output650' not in /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 INFO 2020-02-11 01:45:59,055Z lrauvNc4ToNetcdf.py processResampleNc4File():1025 Variable concentration_of_chromophoric_dissolved_organic_matter_in_sea_water empty so skipping INFO 2020-02-11 01:45:59,063Z lrauvNc4ToNetcdf.py processResampleNc4File():1025 Variable mass_concentration_of_chlorophyll_in_sea_water empty so skipping INFO 2020-02-11 01:45:59,066Z lrauvNc4ToNetcdf.py processResampleNc4File():1025 Variable BackscatteringCoeff700nm empty so skipping INFO 2020-02-11 01:45:59,070Z lrauvNc4ToNetcdf.py processResampleNc4File():1025 Variable VolumeScatCoeff117deg700nm empty so skipping INFO 2020-02-11 01:45:59,073Z lrauvNc4ToNetcdf.py processResampleNc4File():1025 Variable mass_concentration_of_petroleum_hydrocarbons_in_sea_water empty so skipping INFO 2020-02-11 01:45:59,074Z lrauvNc4ToNetcdf.py nudge_coords():609 /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642.nc4 DEBUG 2020-02-11 01:45:59,579Z lrauvNc4ToNetcdf.py var_series():597 longitude: rad_to_deg = True DEBUG 2020-02-11 01:46:00,007Z lrauvNc4ToNetcdf.py var_series():597 latitude: rad_to_deg = True DEBUG 2020-02-11 01:46:00,051Z lrauvNc4ToNetcdf.py var_series():597 longitude_fix: rad_to_deg = False DEBUG 2020-02-11 01:46:00,091Z lrauvNc4ToNetcdf.py var_series():597 latitude_fix: rad_to_deg = False INFO 2020-02-11 01:46:00,092Z lrauvNc4ToNetcdf.py nudge_coords():627 seg# end_sec_diff end_lon_diff end_lat_diff len(segi) seg_min u_drift (cm/s) v_drift (cm/s) start datetime of segment INFO 2020-02-11 01:46:00,096Z lrauvNc4ToNetcdf.py nudge_coords():643 - - - 31232 210.53 - - - INFO 2020-02-11 01:46:00,098Z lrauvNc4ToNetcdf.py nudge_coords():695 1: - - - 464 3.12 - - INFO 2020-02-11 01:46:00,098Z lrauvNc4ToNetcdf.py nudge_coords():699 Points in final series = 31696 DEBUG 2020-02-11 01:46:00,099Z lrauvNc4ToNetcdf.py trackingdb_lat_lon():525 Constructing trackingdb url to 3600 seconds beyond time range of file INFO 2020-02-11 01:46:00,118Z lrauvNc4ToNetcdf.py trackingdb_lat_lon():533 http://odss.mbari.org/trackingdb/position/whoidhs_ac/between/20200206T120832/20200206T174211/data.csv INFO 2020-02-11 01:46:00,137Z lrauvNc4ToNetcdf.py trackingdb_lat_lon():556 Found 0 position values from the Tracking database INFO 2020-02-11 01:46:00,142Z lrauvNc4ToNetcdf.py processResampleNc4File():1120 ['PAR', 'latitude', 'longitude', 'depth', 'time'] DEBUG 2020-02-11 01:46:00,144Z lrauvNc4ToNetcdf.py write_netcdf():120 Creating netCDF file /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642_10S_sci.nc DEBUG 2020-02-11 01:46:00,150Z lrauvNc4ToNetcdf.py write_netcdf():144 Adding in record variable time DEBUG 2020-02-11 01:46:00,253Z lrauvNc4ToNetcdf.py write_netcdf():156 Adding in record variable PAR DEBUG 2020-02-11 01:46:00,264Z lrauvNc4ToNetcdf.py write_netcdf():156 Adding in record variable latitude DEBUG 2020-02-11 01:46:00,274Z lrauvNc4ToNetcdf.py write_netcdf():156 Adding in record variable longitude DEBUG 2020-02-11 01:46:00,285Z lrauvNc4ToNetcdf.py write_netcdf():156 Adding in record variable depth DEBUG 2020-02-11 01:46:00,295Z lrauvNc4ToNetcdf.py write_netcdf():163 Adding in global metadata INFO 2020-02-11 01:46:00,515Z lrauvNc4ToNetcdf.py processResampleNc4File():1123 Wrote /mbari/LRAUV/whoidhs/missionlogs/2020/20200204_20200206/20200206T130832/202002061308_202002061642_10S_sci.nc