From b34e753f41bed5be0467d0b8025657c294c7c557 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:30:47 +0000 Subject: [PATCH 01/44] add link to readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d0245be..7ab77f0 100644 --- a/README.md +++ b/README.md @@ -6,4 +6,4 @@ While the `pints.toy` module already includes a number of simple models and dist ## Models and data -Hydrology +[Rainfall runoff model and river discharge data for the French Broad River at Asheville, North Carolina.](streamflow/) From d0c7e6e5a412a7e4c6348355dda3069d2aa90e2a Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:32:34 +0000 Subject: [PATCH 02/44] change path in run tests --- run-tests.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/run-tests.py b/run-tests.py index 7b8f811..724c311 100644 --- a/run-tests.py +++ b/run-tests.py @@ -12,7 +12,7 @@ def run_unit_tests(): """ Runs unit tests (without subprocesses). """ - model_dirs = ['streamflow/pystreamflow'] + model_dirs = [os.path.join('streamflow', 'pystreamflow')] for dir in model_dirs: tests = os.path.join(dir, 'tests') From d7e1edeb7bbc84e2c6b7b0caa2ad1db9f4ac806f Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:34:54 +0000 Subject: [PATCH 03/44] add data file and description --- streamflow/pystreamflow/data/03451500.dly | 2557 +++++++++++++++++++++ streamflow/pystreamflow/data/README.md | 8 + 2 files changed, 2565 insertions(+) create mode 100644 streamflow/pystreamflow/data/03451500.dly create mode 100644 streamflow/pystreamflow/data/README.md diff --git a/streamflow/pystreamflow/data/03451500.dly b/streamflow/pystreamflow/data/03451500.dly new file mode 100644 index 0000000..e794e78 --- /dev/null +++ b/streamflow/pystreamflow/data/03451500.dly @@ -0,0 +1,2557 @@ +1960 1 1 0 0.67 1.8907 1.7667 -7.25 +1960 1 2 14.53 0.68 1.821 6.0778 -3.1667 +1960 1 3 7.51 0.683 2.7863 9.3833 0.2667 +1960 1 4 0.29 0.687 3.254 4.5056 -3.6389 +1960 1 5 17.23 0.692 2.6072 3.9889 -1.3778 +1960 1 6 7.68 0.697 3.3535 4.3167 -0.5667 +1960 1 7 4.03 0.702 3.4331 7.3889 0.85 +1960 1 8 0.01 0.708 3.045 10.9 -2.6556 +1960 1 9 0 0.714 2.6868 14.6222 -4.7111 +1960 1 10 0.01 0.721 2.4479 16.2944 -0.8389 +1960 1 11 0.02 0.728 2.3086 17.4278 3.5778 +1960 1 12 0.06 0.735 2.1892 14.1167 3.8611 +1960 1 13 1.65 0.744 2.0897 20.1167 6.1611 +1960 1 14 0.24 0.752 2.0201 17.0222 5.2056 +1960 1 15 5 0.761 1.9902 17.3833 7.8222 +1960 1 16 0.1 0.77 1.9802 11.15 0.3444 +1960 1 17 9.15 0.78 1.8608 8.5389 -0.8222 +1960 1 18 3.43 0.79 2.0698 11.3722 1.8611 +1960 1 19 0.07 0.801 2.1892 4.8111 -4.1444 +1960 1 20 0.18 0.812 1.9504 1.0889 -8.0778 +1960 1 21 0.2 0.823 1.8409 0.6389 -9.4667 +1960 1 22 0.12 0.835 1.7514 -3.0722 -9.6778 +1960 1 23 0.02 0.848 1.632 1.2278 -12.6333 +1960 1 24 0 0.86 1.632 0.8222 -10.3444 +1960 1 25 0 0.873 1.5822 5.8944 -11.8167 +1960 1 26 0 0.887 1.5623 13.95 -7.9778 +1960 1 27 9.1 0.901 1.5822 10.1944 -1.5167 +1960 1 28 0.27 0.915 1.7812 12.3667 1.2778 +1960 1 29 18.6 0.93 1.7414 9.3611 2.7278 +1960 1 30 18.74 0.945 2.8261 7.3389 3.7667 +1960 1 31 13.33 0.961 5.493 11.3 2.9833 +1960 2 1 0.11 0.976 5.2342 14.8 -1.5111 +1960 2 2 0.04 0.993 3.5923 15.9556 -1.45 +1960 2 3 0.17 1.009 2.9753 9.7667 -1.2889 +1960 2 4 8.16 1.026 2.647 4.1389 -0.9611 +1960 2 5 51.28 1.044 5.7616 8.0944 0.8167 +1960 2 6 0.4 1.061 8.9758 9.6889 1.8556 +1960 2 7 0.03 1.079 7.4334 6.4333 -2.8111 +1960 2 8 0.01 1.098 5.1745 11.6056 -8.3056 +1960 2 9 0.4 1.116 3.7217 13.0667 -1.7444 +1960 2 10 39.61 1.135 3.8311 13.1556 6.0389 +1960 2 11 0.05 1.155 6.5876 10.7444 0.3833 +1960 2 12 0.05 1.174 6.1497 9.3222 -5.4444 +1960 2 13 32.47 1.194 5.1745 5.0444 -3.5778 +1960 2 14 0.17 1.215 4.259 -1.1222 -8.4556 +1960 2 15 0.35 1.235 3.662 5.3333 -13.2 +1960 2 16 0.29 1.256 3.3734 8.2444 -7.7611 +1960 2 17 0.01 1.277 3.4231 11.4667 -3.5778 +1960 2 18 26.49 1.299 5.0352 7.4889 -1.6056 +1960 2 19 0.05 1.321 6.1895 1.9 -7.0722 +1960 2 20 0.12 1.343 4.5576 5.4056 -9.4833 +1960 2 21 4.46 1.365 3.7416 4.1944 -3.3611 +1960 2 22 0.34 1.387 3.5525 5.6611 -1.6333 +1960 2 23 0.06 1.41 3.2639 9.3833 -7.65 +1960 2 24 3.36 1.433 3.0848 11.7056 -5.4722 +1960 2 25 9.17 1.457 3.4032 8.9944 0.4 +1960 2 26 0.18 1.48 3.8709 5.2389 -3.1611 +1960 2 27 0.37 1.504 3.453 4.8556 -6.8944 +1960 2 28 0.19 1.528 3.1644 10.0278 -2.2278 +1960 2 29 0.03 1.552 3.045 8.35 -2.4389 +1960 3 1 0.01 1.576 2.8957 4.7333 -7.7944 +1960 3 2 54.6 1.601 2.846 1.2167 -6.7556 +1960 3 3 4.7 1.626 3.0649 1.5944 -6.8222 +1960 3 4 0.38 1.651 2.9853 -2.1222 -10.7056 +1960 3 5 0 1.676 2.4877 -4.6389 -15.3389 +1960 3 6 0.01 1.701 2.3882 -0.7611 -14.5222 +1960 3 7 0.87 1.726 2.3584 0.9389 -10.9667 +1960 3 8 0.05 1.752 2.3982 1.9778 -11.6 +1960 3 9 19.1 1.778 2.4579 -0.2222 -8.1389 +1960 3 10 0.1 1.803 2.4579 4.55 -7.8333 +1960 3 11 6.24 1.829 2.4579 2.3889 -4.9556 +1960 3 12 0.23 1.856 2.3982 -0.0278 -7.4444 +1960 3 13 0 1.882 2.3285 4.95 -11.5167 +1960 3 14 0.29 1.908 2.3584 6.8222 -11.65 +1960 3 15 1.15 1.935 2.4479 3.85 -3.2444 +1960 3 16 17.74 1.961 2.6271 2.5167 -1.8611 +1960 3 17 0.07 1.988 3.0848 11.3056 -1.8667 +1960 3 18 0.08 2.014 3.9008 7.2667 -2.5333 +1960 3 19 0.64 2.041 3.3435 5.6222 -7.5111 +1960 3 20 0.54 2.068 3.0848 3.6556 -4.4278 +1960 3 21 2.69 2.095 2.9057 2.5333 -7.0889 +1960 3 22 0.21 2.122 2.8957 9.0722 -6.7333 +1960 3 23 0 2.149 3.443 9.3167 -7.8389 +1960 3 24 0 2.176 3.5525 14.5389 -4.4889 +1960 3 25 0.06 2.203 3.7117 10.6444 -4.4778 +1960 3 26 0.09 2.23 3.5227 15.5667 -1.4889 +1960 3 27 0.02 2.257 3.6122 20.15 -3.1 +1960 3 28 0.04 2.283 3.7416 21.4944 3.0389 +1960 3 29 14.02 2.31 4.06 17.85 7.6333 +1960 3 30 33.57 2.337 6.7965 19.1444 10.4667 +1960 3 31 0.28 2.364 8.6574 16.7111 4.8833 +1960 4 1 0.08 2.391 7.7021 20.9111 2.3389 +1960 4 2 6.6 2.418 6.2791 17.7611 7.1056 +1960 4 3 34.14 2.445 6.1597 16.0889 10.1722 +1960 4 4 18.21 2.472 8.5181 16.5167 10.2444 +1960 4 5 2.13 2.498 8.9758 12.0889 2.8389 +1960 4 6 0.03 2.525 8.1101 17.7056 0.0556 +1960 4 7 0.05 2.551 6.4681 20.8 6.4167 +1960 4 8 0 2.578 4.8859 20.0333 2.6278 +1960 4 9 0 2.604 4.2192 15.6944 3.6333 +1960 4 10 0 2.63 3.8411 10.8111 -3.7556 +1960 4 11 0 2.656 3.5625 17.0667 -5.8611 +1960 4 12 0 2.682 3.3933 23.4389 1.4778 +1960 4 13 0 2.708 3.254 26.2 4.5444 +1960 4 14 0 2.734 3.1047 25.4778 5.3778 +1960 4 15 0 2.759 3.0052 23.1944 6.4278 +1960 4 16 0 2.785 2.9256 24.5778 7.2667 +1960 4 17 0.05 2.81 2.836 25.2056 8.1889 +1960 4 18 0.55 2.835 2.7763 19.5611 7.0167 +1960 4 19 0.03 2.86 2.6569 19.6333 -0.2556 +1960 4 20 0.05 2.885 2.5574 21.1556 4.2556 +1960 4 21 7.17 2.909 2.5375 21.7778 7.7611 +1960 4 22 0 2.934 2.647 26.0833 7.6667 +1960 4 23 0 2.958 2.4678 28.5889 8.1278 +1960 4 24 0 2.982 2.3783 28.6556 9.3278 +1960 4 25 0.03 3.005 2.3285 29.1111 9.7111 +1960 4 26 2.57 3.029 2.3086 28.0389 10.9833 +1960 4 27 7 3.052 2.3186 21.2167 11.6 +1960 4 28 2.22 3.075 2.428 18.7667 8.7389 +1960 4 29 0.39 3.098 2.239 21.25 3.7611 +1960 4 30 7.85 3.12 2.1494 17.6278 8.4944 +1960 5 1 8.15 3.143 2.5574 18.3111 9.7833 +1960 5 2 0 3.165 2.4181 18.3 1.5778 +1960 5 3 0 3.186 2.1892 20.1333 4.4889 +1960 5 4 0 3.208 2.1096 21.5056 3.7222 +1960 5 5 0 3.229 2.04 19.9722 4.4556 +1960 5 6 0.1 3.25 2.0002 20.1167 7.4611 +1960 5 7 36.52 3.27 2.0101 17.4167 10.7444 +1960 5 8 4.84 3.29 3.6918 13.8222 4.9944 +1960 5 9 0.01 3.31 3.3535 16.5444 1.7278 +1960 5 10 0 3.33 2.5574 17.5833 2.1 +1960 5 11 0.03 3.349 2.3086 13.5556 3.6111 +1960 5 12 3.64 3.368 2.1693 9.3944 4.1778 +1960 5 13 0.05 3.387 2.1395 14.6111 -0.3111 +1960 5 14 0.01 3.405 2.0599 21.0556 -0.1056 +1960 5 15 0 3.423 1.9504 25.2444 4.8611 +1960 5 16 0 3.441 1.8907 27.0389 7.9778 +1960 5 17 0 3.458 1.821 29.5611 10.85 +1960 5 18 0.4 3.475 1.7713 29.2389 13.2833 +1960 5 19 0.14 3.492 1.7116 26.5389 13.3167 +1960 5 20 1.48 3.508 1.6519 27.7889 12.9833 +1960 5 21 0.05 3.523 1.5822 27.8389 13.6722 +1960 5 22 0 3.539 1.5325 28.9944 8.7778 +1960 5 23 0.07 3.554 1.4926 27.5444 9.1389 +1960 5 24 3.09 3.569 1.4727 29.8556 10.3278 +1960 5 25 3.34 3.583 1.4628 28.3944 12.2 +1960 5 26 4.97 3.597 1.632 28.4889 11.6667 +1960 5 27 14.68 3.61 1.6519 22.65 13.2722 +1960 5 28 0.89 3.623 1.8111 23.4278 7.9556 +1960 5 29 3.07 3.636 1.5723 25.2167 10.2333 +1960 5 30 0.02 3.648 1.4926 27.3889 11.5444 +1960 5 31 0 3.66 1.423 25.6111 10.8778 +1960 6 1 0.04 3.671 1.3334 26.5167 9.1611 +1960 6 2 2.27 3.682 1.2439 25.1556 11.0611 +1960 6 3 6.28 3.693 1.2737 25.6 12.9 +1960 6 4 3.44 3.703 1.4329 25.9111 15.1889 +1960 6 5 14.16 3.713 1.7215 26.1167 15.1944 +1960 6 6 4.47 3.722 1.8807 27.9667 13.7778 +1960 6 7 1.68 3.731 1.7713 26.3889 13.7278 +1960 6 8 6.03 3.739 1.5126 21.7944 14.7111 +1960 6 9 0.02 3.747 1.632 23.85 12.5667 +1960 6 10 0.01 3.755 1.4727 24.7111 10.1111 +1960 6 11 0.03 3.762 1.3334 26.1944 11.6 +1960 6 12 0.08 3.768 1.2936 28.8778 15.4667 +1960 6 13 0.06 3.774 1.2041 28.8111 14.95 +1960 6 14 1.44 3.78 1.1444 27.4833 15.4778 +1960 6 15 0.01 3.785 1.1344 26.1389 12.8722 +1960 6 16 0.64 3.79 1.0847 29.4611 10.3889 +1960 6 17 0.46 3.795 1.0449 27.6056 15.1389 +1960 6 18 0.03 3.798 0.9931 28.3111 13.5056 +1960 6 19 0.7 3.802 0.9593 29.8278 13.6 +1960 6 20 12.65 3.805 1.1046 29.8056 15.0389 +1960 6 21 16.15 3.807 1.4031 26.9722 16.9 +1960 6 22 7.72 3.809 1.6419 28.2444 15.3833 +1960 6 23 13.76 3.811 1.7414 26.9389 16.1778 +1960 6 24 10.95 3.812 1.8807 31 16.6722 +1960 6 25 3.01 3.813 1.5424 27.1278 16.4222 +1960 6 26 21.92 3.813 1.8111 22.2333 14.05 +1960 6 27 0.15 3.813 2.1196 25.4833 14.4667 +1960 6 28 1.71 3.812 1.7116 24.1833 14.2 +1960 6 29 0.28 3.811 1.4926 28.4278 15.7 +1960 6 30 0.37 3.809 1.3135 29.1778 15.0556 +1960 7 1 5.32 3.807 1.224 29.5944 16.45 +1960 7 2 3.88 3.804 1.3732 29.8944 17.9556 +1960 7 3 0.89 3.801 1.1941 30.7222 16.3 +1960 7 4 1.56 3.798 1.0847 28.5444 16.1944 +1960 7 5 0.38 3.794 1.0747 27.6 16.5889 +1960 7 6 4.39 3.789 1.1643 24.3444 16.8056 +1960 7 7 2.63 3.785 1.1145 26.15 15.8444 +1960 7 8 0.01 3.779 1.0747 26.1944 14.6611 +1960 7 9 1.41 3.773 1.015 25.8 16.4 +1960 7 10 21.38 3.767 1.1444 23.0944 16.5556 +1960 7 11 5.69 3.76 1.5424 26.3722 16.3778 +1960 7 12 0.01 3.753 1.3434 27.35 15.2556 +1960 7 13 2.22 3.746 1.0747 29.0944 16.0167 +1960 7 14 0.6 3.738 1.2737 27.3389 17.8278 +1960 7 15 0.6 3.729 1.0051 26.7944 12.9667 +1960 7 16 1.18 3.72 0.9364 26.2278 15.75 +1960 7 17 1.57 3.711 0.9135 27.5222 14.0667 +1960 7 18 0.33 3.701 0.9473 28.1556 15.3278 +1960 7 19 3.27 3.691 0.8687 28.7778 15.4 +1960 7 20 0.89 3.68 0.9364 28.9556 16.7722 +1960 7 21 0.31 3.669 0.8468 29.35 14.7389 +1960 7 22 3.29 3.658 0.8249 29.8556 16.2667 +1960 7 23 11.33 3.646 0.9931 28.5 16.8111 +1960 7 24 1.93 3.634 1.1941 28.8667 16.8333 +1960 7 25 8.55 3.621 1.025 29.7389 17.1889 +1960 7 26 4.66 3.608 1.0449 28.6056 18.2722 +1960 7 27 4.11 3.594 1.1643 27.9278 17.8722 +1960 7 28 3.82 3.58 1.1344 25.3 15.7389 +1960 7 29 2.69 3.566 1.1046 25.4222 16.55 +1960 7 30 0.8 3.551 1.0449 28.2333 13.7833 +1960 7 31 0.62 3.536 0.9135 29.6 15.2056 +1960 8 1 1.7 3.521 0.8578 29.8056 15.7 +1960 8 2 2.6 3.505 0.8906 30.4056 16.4111 +1960 8 3 2.96 3.489 0.9712 30.5 16.6 +1960 8 4 3.42 3.472 0.9135 30.1889 18.0611 +1960 8 5 3.99 3.455 0.9364 28.8056 17.6167 +1960 8 6 5.06 3.438 0.9016 29.15 16.8 +1960 8 7 10.51 3.42 1.1344 28.7 17.2611 +1960 8 8 6.12 3.402 1.1643 29.0444 16.8389 +1960 8 9 14.15 3.384 1.0747 29.8333 17.2389 +1960 8 10 16.36 3.365 1.9205 28.0778 17.0722 +1960 8 11 22.72 3.346 2.4877 23.4056 17.7611 +1960 8 12 62.83 3.327 3.8908 23.6111 17.0278 +1960 8 13 9.93 3.307 7.7916 26.3778 17.3667 +1960 8 14 5.3 3.287 6.0701 27.85 16.2667 +1960 8 15 2.04 3.267 3.5127 27.6944 16.1889 +1960 8 16 2.76 3.246 2.5276 28.5278 15.4611 +1960 8 17 2.04 3.225 2.2091 26.45 16.4722 +1960 8 18 6.87 3.204 2.1395 26.25 16.1833 +1960 8 19 5.72 3.182 2.5475 27.1833 15.7167 +1960 8 20 1.96 3.161 2.438 27.8722 15.7611 +1960 8 21 8.35 3.139 1.8111 27.6667 16.1111 +1960 8 22 9.29 3.116 1.7215 25.8222 17.6278 +1960 8 23 0.74 3.094 2.2589 26.7222 17.7167 +1960 8 24 2.35 3.071 1.9902 26.6944 15.0333 +1960 8 25 0.11 3.048 1.7016 24.7 15.8056 +1960 8 26 0.03 3.025 1.4528 26.1889 13.4611 +1960 8 27 0.7 3.001 1.2936 27.5833 15.7778 +1960 8 28 0.29 2.977 1.2538 29.1944 15.9556 +1960 8 29 0.75 2.954 1.1941 28.6778 16.5333 +1960 8 30 0.95 2.929 1.1444 30.5056 15.7667 +1960 8 31 2.58 2.905 1.1046 29.3278 16.6 +1960 9 1 16.28 2.88 1.3434 27.4 17.3944 +1960 9 2 3.99 2.856 1.6021 28.4333 16.1111 +1960 9 3 1.31 2.831 1.5325 28.1556 14.8667 +1960 9 4 5.44 2.806 1.4528 28.5667 16.2722 +1960 9 5 1.01 2.78 1.3633 29.6111 15.3944 +1960 9 6 2.93 2.755 1.1444 30.5167 15.5889 +1960 9 7 1.49 2.729 1.0648 26.8056 18.0611 +1960 9 8 1.8 2.704 1.0548 26.5944 17.3833 +1960 9 9 0.89 2.678 1.0051 28.1722 16.7056 +1960 9 10 7.46 2.652 1.015 27.6778 16.3889 +1960 9 11 2.63 2.626 1.1444 25.4056 16.45 +1960 9 12 0.03 2.599 1.0648 23.4389 15.0278 +1960 9 13 0 2.573 0.9593 22.1111 9.1889 +1960 9 14 0 2.547 0.8906 20.3667 5.5222 +1960 9 15 0.04 2.52 0.8468 21.15 8.9722 +1960 9 16 9.46 2.494 0.8687 20.5222 14.3667 +1960 9 17 7.34 2.467 0.9712 19.3722 13.8222 +1960 9 18 7.02 2.44 1.4628 25.1167 15.6056 +1960 9 19 0.95 2.413 1.4031 26.9444 15.6889 +1960 9 20 0.12 2.386 1.224 27.0611 13.1833 +1960 9 21 0.01 2.36 1.0847 26.4944 11.5111 +1960 9 22 0.48 2.333 0.9712 22.85 14.4167 +1960 9 23 0.02 2.306 0.9473 23.4556 14.2611 +1960 9 24 0.02 2.279 0.9254 22.6889 10.7389 +1960 9 25 0.01 2.252 0.8578 21.6444 10.7611 +1960 9 26 0.05 2.225 0.7921 21.7556 9.35 +1960 9 27 9.14 2.198 0.8359 17.2944 10.3722 +1960 9 28 17.93 2.171 1.1941 17.65 11.8722 +1960 9 29 10.7 2.144 1.5723 21.3722 12.8722 +1960 9 30 0.09 2.117 1.6121 24.1944 13.3833 +1960 10 1 0.01 2.09 1.2439 24.2667 9.5056 +1960 10 2 0.2 2.063 1.0449 24.3889 13.0444 +1960 10 3 16.91 2.036 1.214 25.8722 12.2278 +1960 10 4 4.64 2.01 1.9106 23.2833 10.4222 +1960 10 5 13.35 1.983 1.4329 21.6056 10.6167 +1960 10 6 12.83 1.956 2.2489 22.6222 13.5111 +1960 10 7 6.86 1.93 2.4479 19.8611 14.6111 +1960 10 8 19.78 1.903 2.7365 19.1444 13.6611 +1960 10 9 8.95 1.877 3.3535 22.1111 12.6333 +1960 10 10 0.21 1.851 2.9256 22.1722 11.9667 +1960 10 11 0 1.825 2.1992 23.1833 9.0444 +1960 10 12 0.38 1.799 1.8409 24.9611 6.8222 +1960 10 13 0.12 1.773 1.632 24.6222 8.6611 +1960 10 14 0.03 1.747 1.5026 23.8389 9.8167 +1960 10 15 0.04 1.722 1.3633 22.2667 10.9056 +1960 10 16 0.73 1.696 1.2737 23.8 10.1667 +1960 10 17 0 1.671 1.224 22.7833 10.4278 +1960 10 18 0.04 1.646 1.224 22.5833 7.5 +1960 10 19 5.92 1.621 1.1742 19.7889 8.0889 +1960 10 20 15.82 1.596 1.7016 15.7444 7.7222 +1960 10 21 0.04 1.572 1.7116 14.1833 -0.0556 +1960 10 22 0 1.548 1.3235 15.6889 0.4167 +1960 10 23 0 1.523 1.224 19.5611 3.2833 +1960 10 24 0 1.5 1.1742 18.3889 4.5889 +1960 10 25 0.02 1.476 1.1046 17.35 -1.7056 +1960 10 26 3.16 1.452 1.0548 14.0111 -0.1611 +1960 10 27 9.45 1.429 1.1145 13.4444 5.1444 +1960 10 28 1.42 1.406 1.3135 15.0944 5.3667 +1960 10 29 0.03 1.383 1.2041 18.0667 2.4611 +1960 10 30 0.09 1.361 1.1145 18.4333 5.0389 +1960 10 31 14.34 1.339 1.1245 13.7056 6.7611 +1960 11 1 0.04 1.317 1.6121 15.6611 2.4722 +1960 11 2 2.36 1.295 1.4628 20.0833 0.0222 +1960 11 3 0.04 1.274 1.2936 15.8833 1.4833 +1960 11 4 0.03 1.252 1.2339 16.7222 -2.5444 +1960 11 5 1.32 1.232 1.1444 19.1 -1.4833 +1960 11 6 0.05 1.211 1.1046 12.9 -1.8222 +1960 11 7 0.11 1.191 1.0648 7.7167 -2.85 +1960 11 8 0.01 1.171 1.025 9.2722 -7.0333 +1960 11 9 1.97 1.151 1.224 11.9556 -2.4333 +1960 11 10 5.02 1.132 1.0946 13.4056 3.3167 +1960 11 11 0 1.113 1.1543 9.4722 -2.2333 +1960 11 12 0 1.094 1.0946 15.5 -4.6389 +1960 11 13 0 1.076 1.0449 15.6611 -3.1056 +1960 11 14 0 1.058 1.0349 19.7 -2.3278 +1960 11 15 0 1.04 1.0349 19.5833 -0.25 +1960 11 16 0.05 1.023 1.025 18.1611 3.8222 +1960 11 17 0.02 1.006 1.025 16.2889 4.9611 +1960 11 18 0 0.99 0.9911 14.0444 0.2333 +1960 11 19 0 0.974 0.9692 15.1556 -2.1556 +1960 11 20 0 0.958 0.9473 16.0056 -4.1056 +1960 11 21 0 0.942 0.9364 17.5778 -0.6389 +1960 11 22 0.19 0.927 0.9254 18.5778 -1.8333 +1960 11 23 12.07 0.913 1.0051 14.2722 6.5278 +1960 11 24 0.15 0.898 1.1046 12.2389 6.5722 +1960 11 25 0.01 0.885 1.0449 14.9056 4.0611 +1960 11 26 0 0.871 0.9802 17.1556 1.2611 +1960 11 27 0 0.858 0.9692 17.6778 2.2778 +1960 11 28 0.06 0.845 0.9473 20.5944 2.6889 +1960 11 29 2.99 0.833 0.9364 17.6722 6.0111 +1960 11 30 0 0.821 0.9254 7.7 -4.8722 +1960 12 1 0 0.81 0.8836 1.9778 -6.9611 +1960 12 2 0 0.799 0.8737 8.2167 -10.7 +1960 12 3 0 0.788 0.8518 12.9 -10.5444 +1960 12 4 0 0.778 0.8518 16.2111 -7.9944 +1960 12 5 0 0.769 0.8628 17.6111 -4.3222 +1960 12 6 0 0.759 0.8518 17.8056 -1.8111 +1960 12 7 0.03 0.75 0.8518 14.8722 1.0389 +1960 12 8 0 0.742 0.8419 10.7056 0.3167 +1960 12 9 0 0.734 0.8319 7.0778 -6.4667 +1960 12 10 0 0.727 0.81 11.1722 -9.2111 +1960 12 11 37.34 0.72 1.1145 8.0389 -2.1111 +1960 12 12 0.36 0.713 2.0798 3.0722 -6.3667 +1960 12 13 0.01 0.707 1.4926 -2.2778 -12.4444 +1960 12 14 0 0.701 1.2041 8.7389 -12.3611 +1960 12 15 0.57 0.696 1.1941 6.2278 -3.8889 +1960 12 16 0.23 0.691 1.1543 3.6611 -4.65 +1960 12 17 0 0.687 1.015 6.4333 -9.5778 +1960 12 18 0 0.683 0.9692 7.2056 -9.55 +1960 12 19 0.01 0.679 0.9473 8.8833 -8.5833 +1960 12 20 4.12 0.676 0.9473 7.3611 -4.2333 +1960 12 21 1.51 0.674 0.9802 2.6722 -7.0333 +1960 12 22 0.03 0.672 0.9155 -3.6278 -15.6833 +1960 12 23 0.04 0.67 0.8757 -1.4167 -14.3278 +1960 12 24 0.19 0.669 0.8956 2.15 -8.0278 +1960 12 25 0.08 0.669 0.9055 8.9944 -6.8056 +1960 12 26 0.03 0.668 0.9045 11.6889 -5.8389 +1960 12 27 0 0.669 0.9155 9.5667 -2.4 +1960 12 28 0.01 0.669 0.8936 5.7111 -2.85 +1960 12 29 3.51 0.671 0.8836 9.5833 -0.4 +1960 12 30 0.57 0.672 0.9045 10.4833 0.35 +1960 12 31 20.69 0.674 0.9364 7.7333 -3.7778 +1961 1 1 0.65 0.67 1.5126 8.5222 -1.4167 +1961 1 2 0 0.68 1.6718 9.3333 -4.6389 +1961 1 3 0.01 0.683 1.2837 4.1722 -5.5056 +1961 1 4 0 0.687 1.1444 8.9444 -7.2722 +1961 1 5 0 0.692 1.0847 10.8944 -6.1722 +1961 1 6 0 0.697 1.0349 11.8222 -5.2056 +1961 1 7 0 0.702 1.0051 11.6556 -4.4 +1961 1 8 0 0.708 1.0051 7.6611 -2 +1961 1 9 0 0.714 0.9911 6.9167 -9.2278 +1961 1 10 0 0.721 0.9045 9.5778 -10.4556 +1961 1 11 0 0.728 0.9155 12.8167 -8.5278 +1961 1 12 0 0.735 0.9045 15.2778 -7.1444 +1961 1 13 0.48 0.744 0.8936 11.1556 -6.4667 +1961 1 14 38.85 0.752 1.3334 8.8444 1.5556 +1961 1 15 4.29 0.761 3.2739 10.3167 4.7 +1961 1 16 1.1 0.77 2.4479 6.6778 1.0722 +1961 1 17 0.1 0.78 1.9205 10.2056 -2.1167 +1961 1 18 0.06 0.79 1.6419 12.1611 -2.4333 +1961 1 19 5.65 0.801 1.5126 8.9556 -2.7111 +1961 1 20 0.01 0.812 1.4727 1.3333 -8.8056 +1961 1 21 0.72 0.823 1.3732 -3.5722 -11.3222 +1961 1 22 0.07 0.835 1.2538 -1.0833 -16.0611 +1961 1 23 0.01 0.848 1.1941 6.6667 -8.6556 +1961 1 24 0 0.86 1.1941 9.9667 -5.8722 +1961 1 25 0 0.873 1.0747 1.4444 -12.4556 +1961 1 26 8.9 0.887 1.0449 -0.1056 -8.85 +1961 1 27 0.01 0.901 1.0548 -1.6722 -8.8778 +1961 1 28 0.01 0.915 1.0349 0.3444 -12.4389 +1961 1 29 0 0.93 1.0349 4.8 -9.3444 +1961 1 30 0 0.945 1.015 5.8278 -9.2278 +1961 1 31 0 0.961 0.9911 11.2 -7.9667 +1961 2 1 0 0.976 0.9692 11.1944 -5.5667 +1961 2 2 0.11 0.993 0.9692 7.0556 -5.1778 +1961 2 3 8.89 1.009 0.9692 0.9667 -6.6556 +1961 2 4 0 1.026 0.9802 4.4111 -8.3667 +1961 2 5 0 1.044 0.9473 7.0944 -10.6722 +1961 2 6 0.17 1.061 0.9692 3.4889 -7.8722 +1961 2 7 19.88 1.079 0.9911 1.9833 -2.8611 +1961 2 8 0.79 1.098 1.6618 6.3944 -1.4278 +1961 2 9 0.13 1.116 1.8409 4.1 -2.2444 +1961 2 10 0.14 1.135 1.5026 8.4278 -5.1111 +1961 2 11 0 1.155 1.3533 11.7778 -4.2333 +1961 2 12 0 1.174 1.2538 19.5944 -1.3167 +1961 2 13 0 1.194 1.2339 16.7944 -0.4556 +1961 2 14 0 1.215 1.2737 18.7944 1.8611 +1961 2 15 0 1.235 1.2737 17.4944 3.6167 +1961 2 16 0 1.256 1.2538 20.0556 1.9444 +1961 2 17 0.49 1.277 1.2339 15.7 1.9667 +1961 2 18 18.74 1.299 1.2737 14.1778 6.9 +1961 2 19 8.34 1.321 1.8708 13.7778 7.7611 +1961 2 20 18.56 1.343 2.1693 12.2611 6.0222 +1961 2 21 16.37 1.365 3.7416 9.6889 3.6667 +1961 2 22 8.76 1.387 4.0103 12.6222 5.0167 +1961 2 23 24.83 1.41 5.6124 18.9278 7.8944 +1961 2 24 17.42 1.433 5.7517 18.5389 1.3333 +1961 2 25 49.88 1.457 9.8614 15.4389 0 +1961 2 26 0 1.48 10.349 14.7222 -3.0167 +1961 2 27 0 1.504 8.3887 19.2833 -2.3722 +1961 2 28 4.38 1.528 6.7766 19.5944 1.9167 +1961 3 1 0.1 1.552 3.9903 14.8833 2.2167 +1961 3 2 0 1.576 3.1445 13.4056 -1.7222 +1961 3 3 0 1.601 2.7067 17.3556 -3.1333 +1961 3 4 0 1.626 2.4778 22.7556 4.3556 +1961 3 5 0.12 1.651 2.2987 22.4167 9.9333 +1961 3 6 5.59 1.676 2.1992 20.15 12.6389 +1961 3 7 9.89 1.701 2.1494 19.8167 11.7556 +1961 3 8 29.2 1.726 3.4629 20.2 10.55 +1961 3 9 0.7 1.752 4.259 10.3667 -2.5278 +1961 3 10 0.1 1.778 3.0351 8.8 -3.6167 +1961 3 11 0 1.803 2.6072 15.7611 -4.1333 +1961 3 12 0.08 1.829 2.3783 18.9722 -0.3778 +1961 3 13 5.96 1.856 2.239 16.2 3.8444 +1961 3 14 2.07 1.882 2.2987 13.4111 5.2167 +1961 3 15 0.04 1.908 2.1494 18.2444 -1.2167 +1961 3 16 1.85 1.935 2.0201 15.5111 4.4111 +1961 3 17 0.1 1.961 1.8907 14.4944 -2.5611 +1961 3 18 17.37 1.988 1.9205 8.3889 -1.4611 +1961 3 19 1.17 2.014 2.4678 19.0278 0.6778 +1961 3 20 1.01 2.041 2.4678 17.1444 2.7556 +1961 3 21 14.58 2.068 2.4081 10.3556 3.35 +1961 3 22 0.15 2.095 2.8858 11.3444 2.7111 +1961 3 23 3.51 2.122 2.5873 11.9833 2.7389 +1961 3 24 0.23 2.149 2.3683 8.9667 0.7556 +1961 3 25 0.01 2.176 2.1892 16.6389 -0.0222 +1961 3 26 0 2.203 2.0599 21.15 -1.55 +1961 3 27 0 2.23 1.9504 20.6222 2.7556 +1961 3 28 1.17 2.257 1.8907 18.0056 5.5167 +1961 3 29 0 2.283 1.821 20.4667 4.15 +1961 3 30 0 2.31 1.7514 18.4 3.8389 +1961 3 31 35.59 2.337 2.1693 15.2333 7.0944 +1961 4 1 1.67 2.364 3.4729 11.1667 3.85 +1961 4 2 0.07 2.391 2.9156 11.4611 -0.7611 +1961 4 3 2.89 2.418 2.438 13.7556 -0.2889 +1961 4 4 0.01 2.445 2.2987 10.3 0.1111 +1961 4 5 0.14 2.472 2.1295 17.15 -3.1778 +1961 4 6 0.03 2.498 2.0101 13.5 2.8944 +1961 4 7 0 2.525 1.9404 12.8889 -0.1944 +1961 4 8 0.11 2.551 1.8807 14.5111 -2.4056 +1961 4 9 46.17 2.578 2.3484 10.2889 3.0278 +1961 4 10 0.25 2.604 5.3238 10.6722 3.2722 +1961 4 11 0.04 2.63 4.1894 17.1167 -1.8222 +1961 4 12 32.19 2.656 3.9605 13.3667 3.7889 +1961 4 13 0.51 2.682 5.6124 9.45 3 +1961 4 14 0.58 2.708 4.5775 18.1611 -2.0444 +1961 4 15 16.6 2.734 3.6222 16.3611 4.9167 +1961 4 16 1.38 2.759 4.2192 12.4556 1.2889 +1961 4 17 0.13 2.785 3.8112 13.55 0.0333 +1961 4 18 0.05 2.81 3.254 11.9056 2.2389 +1961 4 19 0 2.835 2.9753 14.5889 0.0556 +1961 4 20 0 2.86 2.6868 17.4722 -1.6722 +1961 4 21 0.62 2.885 2.4479 18.8222 4.0167 +1961 4 22 0 2.909 2.3584 23.4278 6.5 +1961 4 23 1.14 2.934 2.2887 25.9722 10.9333 +1961 4 24 0 2.958 2.1992 28.2556 12.2722 +1961 4 25 0.01 2.982 2.0997 25.2 11.7333 +1961 4 26 1.5 3.005 2.03 22.8556 13.3722 +1961 4 27 6.77 3.029 1.9902 17.8333 5.7833 +1961 4 28 0.01 3.052 1.9902 20.4444 4.7056 +1961 4 29 0.01 3.075 1.8409 16.2667 1.4722 +1961 4 30 0.82 3.098 1.7713 16.2667 1.1167 +1961 5 1 10.64 3.12 1.7812 19.4833 6.2111 +1961 5 2 0.27 3.143 1.9504 16.5167 6.5278 +1961 5 3 0 3.165 1.8708 19.2167 0.4667 +1961 5 4 0.02 3.186 1.7315 20.0556 4.2667 +1961 5 5 0.5 3.208 1.6817 16.8111 7.7167 +1961 5 6 0.89 3.229 1.6718 21.1111 8.3667 +1961 5 7 0.32 3.25 1.6718 25.25 12.3611 +1961 5 8 0.01 3.27 1.6419 26.7389 13.2722 +1961 5 9 15.31 3.29 1.7414 22.3778 12.3889 +1961 5 10 15.51 3.31 1.9404 15.0944 9.3722 +1961 5 11 39.36 3.33 4.2789 19.3556 10.7722 +1961 5 12 10.47 3.349 5.9507 15.6611 8.9667 +1961 5 13 0.09 3.368 4.5277 22.8667 8.7167 +1961 5 14 0.29 3.387 3.3634 26.2611 8.2667 +1961 5 15 2.39 3.405 2.846 24.2056 11.9444 +1961 5 16 0 3.423 2.5773 23.1444 11.6444 +1961 5 17 0.05 3.441 2.3683 24.1556 7.6278 +1961 5 18 1.58 3.458 2.1892 20.5444 12.4667 +1961 5 19 0.01 3.475 2.1494 23.7556 11.4056 +1961 5 20 0 3.492 2.0101 23.8611 9.0833 +1961 5 21 0.04 3.508 1.9106 21.9722 10.2944 +1961 5 22 5.23 3.523 1.8509 20.2722 6.3167 +1961 5 23 0.01 3.539 1.8708 19.8889 9.1278 +1961 5 24 0.08 3.554 1.821 22.8778 4.0611 +1961 5 25 8.28 3.569 1.7016 20.3889 6.15 +1961 5 26 4.5 3.583 1.8409 18.95 9.2889 +1961 5 27 0 3.597 1.8708 15.2167 1.3722 +1961 5 28 0 3.61 1.6419 21.5056 0.55 +1961 5 29 0 3.623 1.5822 23.5667 4.5944 +1961 5 30 0 3.636 1.5424 23.6833 8.4111 +1961 5 31 0 3.648 1.4628 26.0167 5.5611 +1961 6 1 0 3.66 1.4429 28.2278 9.8778 +1961 6 2 0.01 3.671 1.3832 29.2722 11.4389 +1961 6 3 1.2 3.682 1.3135 28.5611 12.1 +1961 6 4 0.25 3.693 1.2936 26.0889 14.1611 +1961 6 5 13.42 3.703 1.413 25.0167 13.3278 +1961 6 6 9.16 3.713 1.5723 26.7556 14.4278 +1961 6 7 0.57 3.722 1.6618 27.4722 14.35 +1961 6 8 2.66 3.731 1.6121 27.5833 13.5944 +1961 6 9 0.65 3.739 1.4429 26.9389 14.25 +1961 6 10 14.96 3.747 1.5424 27.2444 16.3667 +1961 6 11 2.84 3.755 1.622 28.2333 14.5889 +1961 6 12 9.64 3.762 1.5922 27.6222 15.3556 +1961 6 13 10.29 3.768 1.8111 27.75 15.3833 +1961 6 14 1.86 3.774 1.9106 28.5556 14.6944 +1961 6 15 23.26 3.78 1.7116 25.3278 15.2889 +1961 6 16 0.73 3.785 2.03 18.7889 8.5444 +1961 6 17 0.05 3.79 1.9802 19.9167 10.5667 +1961 6 18 0 3.795 1.6419 22.2667 8.6278 +1961 6 19 0.82 3.798 1.4926 24.65 8.1611 +1961 6 20 25.91 3.802 1.413 22.1556 9.7833 +1961 6 21 41.93 3.805 2.8559 22.0778 13.4278 +1961 6 22 0.47 3.807 5.1745 25.3167 14.7 +1961 6 23 0.67 3.809 4.6173 25.0333 11.1111 +1961 6 24 0.18 3.811 2.8559 24.5611 11.0222 +1961 6 25 0.49 3.812 2.2589 25.2111 11.4167 +1961 6 26 23.45 3.813 2.2589 21.3278 12.6833 +1961 6 27 3.48 3.813 2.5873 22.7889 13.6833 +1961 6 28 0.46 3.813 2.4081 23.8389 13.7056 +1961 6 29 0.99 3.812 2.1594 25.9667 12.2278 +1961 6 30 8.11 3.811 1.9404 28.2833 13.0556 +1961 7 1 2.33 3.809 2.0101 28.55 13.6167 +1961 7 2 5.32 3.807 2.2191 28.2389 13.35 +1961 7 3 0.82 3.804 1.9802 25.9667 13.9 +1961 7 4 0.01 3.801 1.7016 27.75 12.1056 +1961 7 5 0.05 3.798 1.5026 29.2 12.0444 +1961 7 6 0.58 3.794 1.4031 28.0389 13.7611 +1961 7 7 12.03 3.789 1.4528 22.85 16.0667 +1961 7 8 0.52 3.785 1.632 26.0056 15.1556 +1961 7 9 0.03 3.779 1.4329 23.8167 11.8667 +1961 7 10 0.05 3.773 1.2837 24.9944 7.7889 +1961 7 11 8.46 3.767 1.224 23.1222 8.7 +1961 7 12 9.37 3.76 1.3732 23.0944 12.4722 +1961 7 13 4.2 3.753 1.5723 26.6556 14.5444 +1961 7 14 4.5 3.746 1.4727 27.7667 14.3333 +1961 7 15 7.79 3.738 1.5822 28.1667 15.1833 +1961 7 16 6.25 3.729 1.5723 27.5667 15.0111 +1961 7 17 2.17 3.72 1.5026 27.6889 15.1833 +1961 7 18 4.18 3.711 1.5325 25.6556 16.1944 +1961 7 19 12.07 3.701 1.5325 26.9111 14.9556 +1961 7 20 6.66 3.691 1.8907 29.5278 14.4222 +1961 7 21 6.83 3.68 2.0599 28.8222 16.4778 +1961 7 22 6.85 3.669 2.5873 28.4056 16.2111 +1961 7 23 3.55 3.658 2.0499 28.9 15.8722 +1961 7 24 4.02 3.646 2.0002 28.6889 16.6444 +1961 7 25 1.89 3.634 1.7215 29.2611 16.3722 +1961 7 26 11.12 3.621 1.6718 28.4167 15.7389 +1961 7 27 0.91 3.608 1.7812 28.65 16.3722 +1961 7 28 0.5 3.594 1.5822 29.3389 15.6056 +1961 7 29 3.26 3.58 1.3832 29.8167 15.1111 +1961 7 30 2.29 3.566 1.3832 29.6833 16.5111 +1961 7 31 2.01 3.551 1.2737 30.5722 17.4611 +1961 8 1 3.72 3.536 1.3235 30.7667 18.0556 +1961 8 2 7.82 3.521 1.4727 29.8389 16.8611 +1961 8 3 13.65 3.505 1.8907 29.3833 17.2222 +1961 8 4 26.5 3.489 2.7863 25.75 18.1778 +1961 8 5 0.51 3.472 4.5775 28.1 16.3611 +1961 8 6 8.03 3.455 2.5873 27.9056 14.8611 +1961 8 7 16.71 3.438 2.2887 26.4611 15.4667 +1961 8 8 5.73 3.42 3.0848 26.9667 16.0111 +1961 8 9 21.89 3.402 3.2838 26.3278 16.2833 +1961 8 10 8.72 3.384 4.5775 27.3167 16.0167 +1961 8 11 4.91 3.365 5.3735 29.0556 16.6833 +1961 8 12 3.87 3.346 4.3784 29.2556 16.15 +1961 8 13 0.04 3.327 2.9853 26.6444 16.75 +1961 8 14 0.01 3.307 2.1395 24.1556 12.8722 +1961 8 15 0 3.287 1.8907 24.4667 12.1722 +1961 8 16 0.42 3.267 1.7215 27.2333 10.75 +1961 8 17 0.24 3.246 1.632 27.6056 12.9778 +1961 8 18 8.2 3.225 1.5126 26.2444 13.0556 +1961 8 19 0.07 3.204 1.7215 25.4333 13.2833 +1961 8 20 2.58 3.182 1.632 21.3222 14.1167 +1961 8 21 13.8 3.161 1.5822 24.3389 11.1167 +1961 8 22 8.72 3.139 1.9802 24.6056 12.9 +1961 8 23 21.38 3.116 2.03 25.5389 13.3556 +1961 8 24 97.63 3.094 8.0703 22.2333 15.7056 +1961 8 25 24.48 3.071 17.6133 22.7611 15.2944 +1961 8 26 7.6 3.048 15.026 25.5444 16.2278 +1961 8 27 5.46 3.025 10.9461 27.0056 16.2278 +1961 8 28 8.76 3.001 8.4782 28.9056 17.4889 +1961 8 29 1.3 2.977 6.7368 29.5056 17.2278 +1961 8 30 10.85 2.954 4.8561 28.9833 16.7056 +1961 8 31 2.95 2.929 4.0003 28.0944 16.5 +1961 9 1 5.17 2.905 4.1894 27.4778 17.7333 +1961 9 2 0.69 2.88 3.7416 29.1167 16.9 +1961 9 3 1.36 2.856 3.0052 29.8056 16.0611 +1961 9 4 1.38 2.831 2.8062 29.2722 16.6556 +1961 9 5 3.91 2.806 2.647 28.3833 17.2444 +1961 9 6 1.23 2.78 2.5873 28.2167 16.4167 +1961 9 7 0.66 2.755 2.3484 28.0889 16.3222 +1961 9 8 0.17 2.729 2.229 27.3556 16.0056 +1961 9 9 0.02 2.704 2.1295 27.1778 16.5222 +1961 9 10 0.03 2.678 2.0201 27.3722 15.2 +1961 9 11 6.51 2.652 1.9802 27.7722 16.6056 +1961 9 12 0.22 2.626 2.1892 28.3389 16.4556 +1961 9 13 0.12 2.599 1.9504 27.0111 15.9556 +1961 9 14 2.94 2.573 1.821 23.9333 15.2778 +1961 9 15 0.23 2.547 1.7912 19.9778 10.0444 +1961 9 16 0.02 2.52 1.6817 19.7833 4.0889 +1961 9 17 0.22 2.494 1.5822 18.6833 4.4056 +1961 9 18 4.82 2.467 1.5723 17.7889 6.2556 +1961 9 19 17 2.44 1.821 19.0167 11.6778 +1961 9 20 0.34 2.413 2.1693 24.3 14.6389 +1961 9 21 0 2.386 1.821 24.7056 10.8056 +1961 9 22 0 2.36 1.6121 27.7 10.8 +1961 9 23 0 2.333 1.5325 28.7667 13.3778 +1961 9 24 0 2.306 1.4727 29.05 14.9722 +1961 9 25 0.31 2.279 1.4329 29.1167 13.2 +1961 9 26 0 2.252 1.4031 26.7889 13.7444 +1961 9 27 0 2.225 1.3334 25.3889 9.3722 +1961 9 28 0 2.198 1.2737 24.9333 8.0278 +1961 9 29 0 2.171 1.2439 23.7389 7.9056 +1961 9 30 0 2.144 1.224 22.4333 9.5111 +1961 10 1 0.01 2.117 1.224 23.7 8.8278 +1961 10 2 1 2.09 1.1444 23.2333 10.0111 +1961 10 3 46.17 2.063 1.6917 17.5278 8.8333 +1961 10 4 0.08 2.036 2.6768 17.2278 5.0278 +1961 10 5 0 2.01 1.8509 18.4111 1.0889 +1961 10 6 0 1.983 1.5524 20.3444 1.9056 +1961 10 7 0 1.956 1.4628 21.1056 2.2944 +1961 10 8 0 1.93 1.4031 21.7778 3.3722 +1961 10 9 0.01 1.903 1.3533 23.4167 4.35 +1961 10 10 0 1.877 1.2837 24.2389 5.5889 +1961 10 11 0 1.851 1.2439 24.1556 6.7278 +1961 10 12 0 1.825 1.2041 24.9278 7.2167 +1961 10 13 0.03 1.799 1.1842 24.9278 8.0111 +1961 10 14 0.48 1.773 1.1742 18.6889 8.15 +1961 10 15 0.01 1.747 1.1344 15.35 0.0056 +1961 10 16 0.01 1.722 1.1145 20.4611 0.8944 +1961 10 17 0.01 1.696 1.1145 22.0111 3.1944 +1961 10 18 0.02 1.671 1.1145 22.8389 3.4333 +1961 10 19 6.24 1.646 1.1145 22.0444 4.2444 +1961 10 20 1.27 1.621 1.1643 14.3167 1.3389 +1961 10 21 0.97 1.596 1.1145 15.9333 2.7333 +1961 10 22 0 1.572 1.0946 17.9167 5.2056 +1961 10 23 0 1.548 1.0747 19.9444 1.0278 +1961 10 24 0.02 1.523 1.0747 21.3833 2.7167 +1961 10 25 0.27 1.5 1.0548 22.2667 4.8278 +1961 10 26 0.05 1.476 1.0449 16.1389 3.4167 +1961 10 27 0 1.452 1.025 16.6167 -3.7333 +1961 10 28 0 1.429 1.025 15.9222 -3.2667 +1961 10 29 0 1.406 1.025 21.3778 3.0389 +1961 10 30 0.07 1.383 1.025 24.1278 5.1833 +1961 10 31 5.2 1.361 1.0747 22.6556 11.2833 +1961 11 1 15.96 1.339 1.3931 23.1222 13.2333 +1961 11 2 0.15 1.317 1.2837 23.0556 10.0056 +1961 11 3 0.31 1.295 1.0946 22.5556 14.6111 +1961 11 4 4.96 1.274 1.0747 22.3611 14.0722 +1961 11 5 0.15 1.252 1.0946 24.3278 12.75 +1961 11 6 6.29 1.232 1.0946 20.8611 12.8056 +1961 11 7 0.01 1.211 1.1444 18.6944 8.7722 +1961 11 8 0.01 1.191 1.0548 12.6667 1.3389 +1961 11 9 0 1.171 1.025 11.8111 -4.7167 +1961 11 10 0 1.151 1.015 16.3611 -1.1056 +1961 11 11 0.05 1.132 1.0051 17.5611 1.3722 +1961 11 12 0.78 1.113 1.0051 19.0889 6.3056 +1961 11 13 10.3 1.094 1.0349 17.6278 8.7111 +1961 11 14 31.73 1.076 1.821 17.7056 12.2 +1961 11 15 2.46 1.058 2.5077 19.3 11.8222 +1961 11 16 14.79 1.04 1.8708 19.2778 13.4333 +1961 11 17 0.04 1.023 2.4081 15.5333 4.3833 +1961 11 18 0.02 1.006 1.9305 9.5944 0.8611 +1961 11 19 0.33 0.99 1.5922 5.3722 0.5222 +1961 11 20 0.01 0.974 1.4628 6.2556 -1.4444 +1961 11 21 0 0.958 1.3732 10.1722 -5.1278 +1961 11 22 0 0.942 1.3135 10.2722 -3.85 +1961 11 23 62.91 0.927 3.5824 11.5278 4.9278 +1961 11 24 0.1 0.913 6.0701 13.0944 3.2722 +1961 11 25 0 0.898 4.3486 16.9222 -1.7222 +1961 11 26 0.01 0.885 2.7465 14.6611 -1.0944 +1961 11 27 1.96 0.871 2.2788 13.9944 2.6167 +1961 11 28 0.03 0.858 2.04 9.6722 -0.8333 +1961 11 29 0 0.845 1.8708 6.7056 -6.8722 +1961 11 30 0 0.833 1.7215 13.0167 -6.5278 +1961 12 1 0.01 0.821 1.6519 13.6444 -3.6222 +1961 12 2 0.55 0.81 1.5922 13.5889 -2.0333 +1961 12 3 0.74 0.799 1.5524 16.7778 3.4556 +1961 12 4 0.04 0.788 1.5225 17.5167 4.4833 +1961 12 5 3.44 0.778 1.5225 14.4333 6.5889 +1961 12 6 2.33 0.769 1.4827 13.2389 2.7167 +1961 12 7 0.01 0.759 1.4429 10.3278 -1.0056 +1961 12 8 0.01 0.75 1.3732 7.9389 -3.9944 +1961 12 9 15.48 0.742 1.3434 5.4111 -1.9778 +1961 12 10 35.08 0.734 2.8758 10.3833 0 +1961 12 11 60.87 0.727 4.8561 10.6556 5.75 +1961 12 12 44.14 0.72 13.1353 12.7111 7.2667 +1961 12 13 1.24 0.713 12.5383 9.7389 -1.2944 +1961 12 14 1.23 0.707 10.4485 6.0778 -5.5778 +1961 12 15 0.85 0.701 7.7021 11.1 -0.1444 +1961 12 16 20.16 0.696 4.7466 8.2 1.0444 +1961 12 17 36.42 0.691 5.2342 11.7056 2.4278 +1961 12 18 17.42 0.687 9.0753 18.2833 6.8389 +1961 12 19 0.07 0.683 8.6375 14.9722 2.4 +1961 12 20 0.01 0.679 6.9259 7.9278 -0.5778 +1961 12 21 0.01 0.676 5.5925 7.2778 -4.7556 +1961 12 22 0 0.674 3.9406 11.0667 -6.4222 +1961 12 23 4.66 0.672 3.5127 8.4056 -3.2778 +1961 12 24 0.09 0.67 3.3336 3.1222 -5.5444 +1961 12 25 0.02 0.669 2.9753 2.6333 -6.7667 +1961 12 26 0.1 0.669 2.7465 12.2556 -9.1778 +1961 12 27 11.92 0.668 2.6669 8.65 -4.1611 +1961 12 28 1.29 0.669 2.8659 3.3611 -5.7778 +1961 12 29 0.11 0.669 2.7266 -1.6778 -12.2778 +1961 12 30 0.05 0.671 2.438 2.25 -11.9778 +1961 12 31 0.13 0.672 2.3186 2.6944 -8.0944 +1962 1 1 17.99 0.67 2.3783 2.3778 -2.0833 +1962 1 2 0.01 0.68 2.3683 1.7889 -6.2222 +1962 1 3 0 0.683 2.2091 11.9611 -8.6 +1962 1 4 0.01 0.687 2.229 11.2056 -3.9444 +1962 1 5 6.34 0.692 2.2489 9.7944 -2.7056 +1962 1 6 33.91 0.697 5.1049 13.4389 1.7444 +1962 1 7 0.01 0.702 7.0155 7.1333 -2.3833 +1962 1 8 1.61 0.708 5.9507 3.25 -3.0278 +1962 1 9 3.52 0.714 4.1496 -0.35 -6.1222 +1962 1 10 1.97 0.721 3.3137 -3.4333 -10.9167 +1962 1 11 0 0.728 2.9455 -2.9778 -15.3556 +1962 1 12 0 0.735 2.7962 0.0167 -11.7667 +1962 1 13 0 0.744 2.6271 5.3722 -13.1 +1962 1 14 0 0.752 2.5276 5.1722 -10.3 +1962 1 15 15.15 0.761 2.8559 11.6722 -2.05 +1962 1 16 0 0.77 3.2739 7.7611 -4.8389 +1962 1 17 0.12 0.78 2.7465 6.4778 -7.4778 +1962 1 18 0.08 0.79 2.5674 4.3278 -5.2222 +1962 1 19 3.45 0.801 2.4877 1.4667 -3.8833 +1962 1 20 0.03 0.812 2.428 7.4111 -2.6 +1962 1 21 0 0.823 2.3186 10.3944 -2.6889 +1962 1 22 2.35 0.835 2.2688 14.9833 0.5278 +1962 1 23 13.42 0.848 2.647 14.7167 5.65 +1962 1 24 12.8 0.86 2.7067 12.7333 0.5944 +1962 1 25 5.36 0.873 3.0251 15.7889 6.15 +1962 1 26 6.63 0.887 3.0251 19.6556 9.4722 +1962 1 27 22.6 0.901 3.8411 15.2944 8.5167 +1962 1 28 12.18 0.915 5.1745 8.7722 -0.5667 +1962 1 29 0 0.93 5.274 11.9444 -4.6222 +1962 1 30 0.05 0.945 4.2789 14.0056 -1.2611 +1962 1 31 0.01 0.961 3.6421 9.1556 -6.8667 +1962 2 1 0.03 0.976 3.2739 15.8389 -4.3222 +1962 2 2 0 0.993 3.0251 14.8111 -2.35 +1962 2 3 0 1.009 2.846 19.2667 -2.6667 +1962 2 4 0 1.026 2.6868 20.7667 0.1778 +1962 2 5 0.89 1.044 2.5873 16.7778 2.0056 +1962 2 6 0 1.061 2.4977 8.4944 -7.2333 +1962 2 7 0.01 1.079 2.3683 3.3167 -11.6722 +1962 2 8 0.21 1.098 2.2887 4.0111 -5.8167 +1962 2 9 8.4 1.116 2.3285 13.1333 -0.6222 +1962 2 10 0 1.135 2.3683 8.0556 -1.9444 +1962 2 11 0.01 1.155 2.1892 6.7333 -9.1556 +1962 2 12 0 1.174 2.1295 17.6333 -3.2444 +1962 2 13 0 1.194 2.0897 14.6278 -1.2667 +1962 2 14 0 1.215 2.0499 18.7611 -0.4222 +1962 2 15 0.08 1.235 1.9902 15.5333 -0.2056 +1962 2 16 3.5 1.256 1.9902 10.5833 0.7556 +1962 2 17 0.03 1.277 1.9902 14.9889 -3.2722 +1962 2 18 8.01 1.299 1.9205 10.9778 -0.0556 +1962 2 19 5.69 1.321 2.1594 17.5611 4 +1962 2 20 0.1 1.343 2.2589 13.6167 -2.1167 +1962 2 21 13.86 1.365 2.0698 9.0444 -0.7556 +1962 2 22 17.48 1.387 3.0649 18.3 3.3667 +1962 2 23 25.98 1.41 4.1695 19.1333 8.2222 +1962 2 24 11.06 1.433 5.0651 18.0611 7.9722 +1962 2 25 29.85 1.457 5.3238 11.9389 1.2222 +1962 2 26 2.32 1.48 7.0652 17.5944 2.9333 +1962 2 27 2.82 1.504 5.9308 20.0611 8.5611 +1962 2 28 5.91 1.528 4.6173 19.8444 10.2056 +1962 3 1 0.18 1.552 3.861 11.0444 2.4278 +1962 3 2 0.08 1.576 3.3833 6.9833 -1.2 +1962 3 3 0.38 1.601 3.0948 6.2944 -2.6778 +1962 3 4 0.8 1.626 2.9256 6.1611 -0.75 +1962 3 5 5.12 1.651 2.9156 5.0944 -2.0722 +1962 3 6 3.06 1.676 2.7863 0.3833 -6.2222 +1962 3 7 0.05 1.701 2.647 6.5222 -3.4944 +1962 3 8 0.7 1.726 2.5276 5.9444 -4.9 +1962 3 9 14.68 1.752 2.5674 5.4389 -2.0056 +1962 3 10 12.56 1.778 2.7365 10.9389 -0.4889 +1962 3 11 19.74 1.803 3.8809 8.35 2.7889 +1962 3 12 1.44 1.829 5.2143 14.9167 2.7444 +1962 3 13 0 1.856 4.8163 12.3278 0.6556 +1962 3 14 0 1.882 3.7416 10.2278 -1.8 +1962 3 15 0 1.908 3.3037 10.0667 1.8667 +1962 3 16 0.31 1.935 3.045 9.5722 -2.2111 +1962 3 17 0.03 1.961 2.8261 7.6889 -3.9944 +1962 3 18 0.02 1.988 2.6868 11.4333 -4.8111 +1962 3 19 1.57 2.014 2.5873 13.3833 -2.6944 +1962 3 20 7.89 2.041 2.5674 15.8889 2.0722 +1962 3 21 16.71 2.068 3.1545 20.3 6.0778 +1962 3 22 0 2.095 3.254 14.7222 3.0722 +1962 3 23 0 2.122 2.7962 14.9389 4.25 +1962 3 24 0.02 2.149 2.6271 18.1167 0.9167 +1962 3 25 6.46 2.176 2.5276 15.4278 2.2556 +1962 3 26 30.03 2.203 3.7714 8.9667 2.9 +1962 3 27 0.05 2.23 5.0949 16.45 0.4389 +1962 3 28 0 2.257 3.7416 18.6444 -1.6611 +1962 3 29 0 2.283 3.2241 20.2444 0.0833 +1962 3 30 6.18 2.31 2.9753 19.7611 7.4722 +1962 3 31 32.57 2.337 3.5724 16.4833 10.8833 +1962 4 1 0.9 2.364 5.5129 12.8722 3.2 +1962 4 2 0.15 2.391 4.7466 8.2278 -2.6333 +1962 4 3 0 2.418 3.7714 11.6389 -3.4611 +1962 4 4 0.02 2.445 3.3833 13.9722 -3.8833 +1962 4 5 5.27 2.472 3.1445 12.7889 0.0056 +1962 4 6 33.35 2.498 3.2042 12.1333 4.4889 +1962 4 7 7.54 2.525 5.6124 18.4611 8.3611 +1962 4 8 6.63 2.551 6.09 19.6167 8.6222 +1962 4 9 0.24 2.578 5.7318 19.4056 6.8667 +1962 4 10 0.17 2.604 4.458 18.6667 6.9 +1962 4 11 44.7 2.63 5.493 17.0889 8.2333 +1962 4 12 9.57 2.656 6.7169 16.1667 9.2556 +1962 4 13 0.16 2.682 6.1696 12.5 2.1944 +1962 4 14 1.07 2.708 5.0651 12.4889 -1.7111 +1962 4 15 3.79 2.734 4.4182 10.3333 0.95 +1962 4 16 0 2.759 4.1297 9.3278 -2.7167 +1962 4 17 0 2.785 3.7615 11.5722 -3.8611 +1962 4 18 0 2.81 3.4729 16.6333 -1.6944 +1962 4 19 0 2.835 3.3137 20.0444 1.45 +1962 4 20 0 2.86 3.1246 15.3111 1.2333 +1962 4 21 0 2.885 2.9753 20.1611 -3.3278 +1962 4 22 0 2.909 2.8858 24.6722 0.1944 +1962 4 23 0.05 2.934 2.7962 24.2222 6.7389 +1962 4 24 0.07 2.958 2.7067 22.2444 3.1056 +1962 4 25 1.14 2.982 2.6171 23.0944 5.2556 +1962 4 26 0.72 3.005 2.6271 23.9222 9.3833 +1962 4 27 0.01 3.029 2.5475 23.5222 7.5889 +1962 4 28 1.06 3.052 2.4678 23.7167 10.1889 +1962 4 29 0.08 3.075 2.4081 24.7722 12.1278 +1962 4 30 0.51 3.098 2.3484 29.1778 9.8167 +1962 5 1 2.94 3.12 2.3882 29.1778 12.1389 +1962 5 2 0.11 3.143 2.2887 22.8944 11.7611 +1962 5 3 0.04 3.165 2.1693 22.0333 3.9056 +1962 5 4 0.83 3.186 2.0997 23.6111 4.7 +1962 5 5 0.82 3.208 2.0897 23.9889 7.1944 +1962 5 6 0 3.229 2.0599 26.5333 5.2444 +1962 5 7 0.09 3.25 1.9902 26.8611 9.0333 +1962 5 8 0.18 3.27 1.9504 29.2333 9.2056 +1962 5 9 4.23 3.29 1.9106 28.4056 12.4722 +1962 5 10 0.99 3.31 1.8807 23.1722 11.9722 +1962 5 11 0.87 3.33 1.9504 25.4333 12.0056 +1962 5 12 3.17 3.349 1.8907 24.8889 10.15 +1962 5 13 0.23 3.368 1.9504 28.4222 13.3778 +1962 5 14 7.44 3.387 1.8509 28.3833 15.1222 +1962 5 15 3.01 3.405 1.9205 29.3556 13.1556 +1962 5 16 4.88 3.423 1.8608 29.5333 12.1 +1962 5 17 1.98 3.441 1.9106 28.9556 11.5 +1962 5 18 1.11 3.458 1.8111 30.2278 13.9778 +1962 5 19 2.7 3.475 1.7414 30.7722 14.2333 +1962 5 20 0.16 3.492 1.6718 29.5056 13.8722 +1962 5 21 2.97 3.508 1.7116 28.8556 13.5333 +1962 5 22 0.27 3.523 1.6121 29.4056 13.6333 +1962 5 23 0.25 3.539 1.5424 28.9389 14.2167 +1962 5 24 3.07 3.554 1.5026 29.3778 12.4167 +1962 5 25 0.83 3.569 1.4727 29.6944 12.2944 +1962 5 26 0.23 3.583 1.413 29.6333 13.3333 +1962 5 27 10.41 3.597 1.413 29.9667 14.6111 +1962 5 28 2.49 3.61 1.5822 27.6444 14.9556 +1962 5 29 0.13 3.623 1.5822 24.2 15.4833 +1962 5 30 13.28 3.636 1.6817 24.9222 15.25 +1962 5 31 9.9 3.648 2.0002 25.0833 15.0667 +1962 6 1 1.67 3.66 1.8409 25.7 14.4667 +1962 6 2 12.7 3.671 1.6817 26.2222 14.7167 +1962 6 3 27.71 3.682 1.9504 24.4833 14.9611 +1962 6 4 15.95 3.693 3.851 23.6278 16.3444 +1962 6 5 6.16 3.703 4.3685 24.15 15.9056 +1962 6 6 1.43 3.713 3.3137 26.1833 13.9 +1962 6 7 1.05 3.722 2.3683 23.2167 13.8333 +1962 6 8 0.14 3.731 2.0698 23.3333 13.7056 +1962 6 9 0.11 3.739 1.8907 23.9667 13.4056 +1962 6 10 0.3 3.747 1.7713 25.0778 14.9889 +1962 6 11 11.73 3.755 1.7414 24.8667 14.1778 +1962 6 12 38.43 3.762 2.6171 23.9889 16.4389 +1962 6 13 10.21 3.768 5.2541 25.2944 16.5278 +1962 6 14 0.24 3.774 3.8212 24.1167 13.8 +1962 6 15 0.15 3.78 2.8659 25.0389 12.6222 +1962 6 16 0.03 3.785 2.3186 26.2611 12.6389 +1962 6 17 0.01 3.79 2.0599 28.85 13.6278 +1962 6 18 0 3.795 1.8608 29.7167 14.4556 +1962 6 19 6.23 3.798 1.7713 29.8556 14.6944 +1962 6 20 9.96 3.802 1.9902 24.85 16.3222 +1962 6 21 0.21 3.805 1.8807 26.9944 13.4722 +1962 6 22 1.21 3.807 1.7016 28.2167 15.8 +1962 6 23 14.98 3.809 1.7812 28.7056 15.8389 +1962 6 24 1.31 3.811 1.9205 27.6556 14.9556 +1962 6 25 14.16 3.812 1.7414 29.3278 13.7 +1962 6 26 5.84 3.813 2.637 27.8833 14.55 +1962 6 27 12.17 3.813 2.0201 21.1556 15.5778 +1962 6 28 20.55 3.813 3.0251 19.9222 13.9944 +1962 6 29 1.7 3.812 2.9654 25.0722 12.1778 +1962 6 30 0 3.811 2.239 25.8833 10.3222 +1962 7 1 0.98 3.809 1.9404 28.0444 12.5278 +1962 7 2 2.97 3.807 1.7315 27.9389 14.1556 +1962 7 3 4.76 3.804 1.6618 27.1 15.6389 +1962 7 4 10.59 3.801 1.9902 28 17.3333 +1962 7 5 0.05 3.798 1.8807 26.2444 16.5889 +1962 7 6 1.6 3.794 1.6618 23.1556 17.5667 +1962 7 7 4.33 3.789 1.6419 28.0611 16.0889 +1962 7 8 10.43 3.785 1.632 27.05 16.7611 +1962 7 9 4.42 3.779 1.9404 28.0333 16.9833 +1962 7 10 0 3.773 1.7016 28.3278 12.8111 +1962 7 11 0.49 3.767 1.4926 29.35 14.7556 +1962 7 12 2.34 3.76 1.4429 28.2833 16.7611 +1962 7 13 0 3.753 1.3633 30.3 15.55 +1962 7 14 0.22 3.746 1.3135 31.2778 14.5444 +1962 7 15 0.1 3.738 1.2339 31.8556 15.3 +1962 7 16 1.24 3.729 1.1842 30.8833 17.3667 +1962 7 17 2.68 3.72 1.1444 29.85 15.95 +1962 7 18 4.31 3.711 1.1543 28.6889 16.6667 +1962 7 19 0.18 3.701 1.2837 28.3 14.6722 +1962 7 20 0.15 3.691 1.2737 29.5722 14.9333 +1962 7 21 0.11 3.68 1.1444 30.3056 16.3667 +1962 7 22 0.01 3.669 1.0449 30.05 14.0611 +1962 7 23 0.44 3.658 0.9583 30.8889 14.1833 +1962 7 24 6.11 3.646 0.9692 30.8944 16.3944 +1962 7 25 23.56 3.634 1.4926 24.7167 17.3611 +1962 7 26 0.3 3.621 1.5026 27.2611 16.35 +1962 7 27 0.1 3.608 1.1444 25.0667 9.9333 +1962 7 28 1.52 3.594 1.025 25.3611 9.95 +1962 7 29 8.26 3.58 1.0449 26.9444 15.3056 +1962 7 30 20.02 3.566 1.1941 28.1444 17.0444 +1962 7 31 0.33 3.551 1.7116 28.0944 16.9556 +1962 8 1 0.43 3.536 1.1543 28.5667 13.2944 +1962 8 2 13.83 3.521 1.025 26.4056 16.6222 +1962 8 3 15.29 3.505 1.413 25.9333 16.45 +1962 8 4 3.1 3.489 1.8907 27.7722 17.6333 +1962 8 5 7.2 3.472 1.4628 29.3333 16.7167 +1962 8 6 4.64 3.455 1.4429 30.1056 16.1722 +1962 8 7 7.7 3.438 1.4628 29.1222 16.4333 +1962 8 8 5.25 3.42 1.2339 28.7222 15.8111 +1962 8 9 0.01 3.402 1.1046 27.8556 16.1111 +1962 8 10 0 3.384 1.0847 26.3444 11.7667 +1962 8 11 0.01 3.365 0.9692 26.3278 10.7889 +1962 8 12 0.06 3.346 0.9364 26.8278 13.4222 +1962 8 13 6.4 3.327 0.9911 27.5333 15.3222 +1962 8 14 5.81 3.307 1.1444 27.6278 15.3389 +1962 8 15 7.26 3.287 1.1643 26.5556 15.6722 +1962 8 16 4.63 3.267 1.3235 26.9889 16.2389 +1962 8 17 1.04 3.246 1.2737 28.2389 14.6222 +1962 8 18 0.43 3.225 1.0548 28.2278 13.2 +1962 8 19 0.78 3.204 0.9802 29.2889 14.3056 +1962 8 20 2.52 3.182 0.9802 30.7 15.4611 +1962 8 21 4.76 3.161 0.9911 29.5889 16.2556 +1962 8 22 0.51 3.139 1.015 28.3611 15.6444 +1962 8 23 12.79 3.116 1.3533 24.6222 16.4944 +1962 8 24 0.06 3.094 1.2737 23.3833 15.2833 +1962 8 25 0.1 3.071 1.0349 25.6778 11.6222 +1962 8 26 0.08 3.048 0.9583 26.6722 13.9944 +1962 8 27 0 3.025 0.9155 27.9 14.7611 +1962 8 28 0 3.001 0.8628 28.8722 14.1111 +1962 8 29 0.03 2.977 0.821 29.2278 11.1333 +1962 8 30 0 2.954 0.7901 29.65 11.0778 +1962 8 31 0 2.929 0.7682 29.0944 12.5111 +1962 9 1 0 2.905 0.7583 29.4389 12.3056 +1962 9 2 0.07 2.88 0.7264 29.4333 12.8278 +1962 9 3 5.75 2.856 0.7264 29.7667 16.0222 +1962 9 4 9.37 2.831 0.8518 29.8444 17.2389 +1962 9 5 2.58 2.806 1.3135 27.1278 17.0222 +1962 9 6 0.08 2.78 0.8628 23.7667 15.0556 +1962 9 7 0.69 2.755 0.8001 21.3222 13.0111 +1962 9 8 0.34 2.729 0.7901 21.15 13.7944 +1962 9 9 1.31 2.704 0.7901 24.6056 16.0667 +1962 9 10 0.59 2.678 0.8001 29.1444 17 +1962 9 11 0.11 2.652 0.7792 29.1333 16.0167 +1962 9 12 0.01 2.626 0.7264 30.1056 13.8556 +1962 9 13 0.16 2.599 0.7065 30.3444 11.3833 +1962 9 14 5.51 2.573 0.7065 29.8111 13.4944 +1962 9 15 8.92 2.547 0.7264 26.9389 15.1444 +1962 9 16 37.19 2.52 0.9155 22.35 15.9333 +1962 9 17 12.63 2.494 1.9404 24.8611 14.1333 +1962 9 18 0.01 2.467 1.9106 23.5444 10.5 +1962 9 19 0.04 2.44 1.1444 23.6556 6.5 +1962 9 20 0 2.413 0.9155 20.55 8.4056 +1962 9 21 0 2.386 0.8518 17.9389 2.6222 +1962 9 22 0 2.36 0.821 20.5111 4.5389 +1962 9 23 0 2.333 0.81 21.6056 7.5333 +1962 9 24 0.06 2.306 0.7483 19.4444 9.35 +1962 9 25 0.43 2.279 0.7483 18.9333 8.25 +1962 9 26 18.52 2.252 0.8836 17.1889 11.9111 +1962 9 27 3.7 2.225 1.1543 17.0722 10.4722 +1962 9 28 0 2.198 1.025 16.3056 4.9167 +1962 9 29 0 2.171 0.8737 19.5167 1.9167 +1962 9 30 0.06 2.144 0.821 20.4722 3.3278 +1962 10 1 0.05 2.117 0.7483 21.4 4.2167 +1962 10 2 37.48 2.09 0.821 18.2778 10.0778 +1962 10 3 25.91 2.063 2.8261 17.7333 13.55 +1962 10 4 25.83 2.036 5.8512 21.9944 14.2278 +1962 10 5 0.09 2.01 5.274 23.2944 10.7222 +1962 10 6 1.08 1.983 2.9057 22.5611 9.7778 +1962 10 7 2.4 1.956 1.9802 25.7833 10.6222 +1962 10 8 0.19 1.93 1.6419 27.3111 12.6944 +1962 10 9 0.12 1.903 1.4528 23.25 11.0556 +1962 10 10 0 1.877 1.3235 25.3889 6.7444 +1962 10 11 0 1.851 1.2339 26.2278 7.2389 +1962 10 12 0 1.825 1.1842 26.0278 7.6389 +1962 10 13 0.01 1.799 1.0847 26.3167 9.5167 +1962 10 14 0 1.773 1.015 25.7833 11.8389 +1962 10 15 0 1.747 0.9254 24.8556 10.1222 +1962 10 16 0 1.722 0.9473 24.6222 10.1778 +1962 10 17 0.38 1.696 0.9473 24.1222 10.5111 +1962 10 18 0 1.671 0.9254 22.2889 5.8389 +1962 10 19 0 1.646 0.9016 21.8 2.8056 +1962 10 20 0.09 1.621 0.8906 23.0167 2.1833 +1962 10 21 14.81 1.596 0.9473 20.55 7.3333 +1962 10 22 0.03 1.572 1.1145 19.45 5.9889 +1962 10 23 0 1.548 0.9593 17.6056 3.6611 +1962 10 24 0 1.523 0.8906 11.2722 -1.7111 +1962 10 25 0 1.5 0.8906 10.6556 -3.0389 +1962 10 26 0 1.476 0.8468 7.8167 -4.9333 +1962 10 27 0 1.452 0.8359 12.7556 -7.1333 +1962 10 28 0 1.429 0.8359 19.5944 -2.7833 +1962 10 29 0.01 1.406 0.803 19.45 3.25 +1962 10 30 1.47 1.383 0.814 20.3167 3.6 +1962 10 31 1.07 1.361 0.8249 14.3722 4.5389 +1962 11 1 0.13 1.339 0.803 12.8278 -2.5056 +1962 11 2 0.1 1.317 0.7921 12.1889 -2.7278 +1962 11 3 0.07 1.295 0.7812 10.7944 0.3056 +1962 11 4 0.02 1.274 0.7812 10.0444 -1.8333 +1962 11 5 2.05 1.252 0.7921 5.6 -1.4333 +1962 11 6 0.02 1.232 0.7812 11.1833 -6.0111 +1962 11 7 2.8 1.211 0.7812 14.4222 -5.3056 +1962 11 8 0.83 1.191 0.7613 12.4222 1.6056 +1962 11 9 65.18 1.171 2.0002 10.9556 5.6333 +1962 11 10 0.73 1.151 4.3088 12.5889 2.2056 +1962 11 11 0.01 1.132 2.4877 16.9722 0.3667 +1962 11 12 0.18 1.113 1.8111 12.55 -1.3389 +1962 11 13 0.01 1.094 1.5623 11.1056 0.2 +1962 11 14 0 1.076 1.413 13.9278 -4.0556 +1962 11 15 0 1.058 1.3334 17.3778 -2.0167 +1962 11 16 0.37 1.04 1.2936 17.2389 1.7833 +1962 11 17 3.78 1.023 1.2538 15.9278 8.2889 +1962 11 18 16.2 1.006 1.4628 13.9278 6.4944 +1962 11 19 0.28 0.99 1.6917 8.7444 -0.1778 +1962 11 20 1.86 0.974 1.4926 10.5889 2.6167 +1962 11 21 21.18 0.958 1.413 13.6278 4.8111 +1962 11 22 0.19 0.942 1.9603 12.6778 4.4889 +1962 11 23 0.01 0.927 2.0499 14.6167 -3.9889 +1962 11 24 0 0.913 1.7116 15.4778 -1.5722 +1962 11 25 0.4 0.898 1.5126 10.6833 1.1 +1962 11 26 0.02 0.885 1.3931 8.7889 -5.5 +1962 11 27 0.01 0.871 1.2339 14.2889 -4.4056 +1962 11 28 2.1 0.858 1.224 12.8556 3.5389 +1962 11 29 0.62 0.845 1.2638 15.5778 7.7556 +1962 11 30 0.04 0.833 1.2737 16.3944 3.6778 +1962 12 1 0 0.821 1.214 18.15 -1.3222 +1962 12 2 0.07 0.81 1.1941 18.3222 -3.8944 +1962 12 3 2.77 0.799 1.1543 15.7889 -2.5889 +1962 12 4 8.33 0.788 1.3931 13.5167 3.7 +1962 12 5 8.32 0.778 1.4727 9.7444 0.3556 +1962 12 6 0.83 0.769 1.5325 0.9056 -6.4222 +1962 12 7 0.04 0.759 1.3334 5.1333 -8.6333 +1962 12 8 0.08 0.75 1.2936 4.7333 -3.9111 +1962 12 9 0.24 0.742 1.3135 1.6944 -6.9056 +1962 12 10 0 0.734 1.2538 -1.2944 -10.8222 +1962 12 11 0.33 0.727 1.1643 -1.1333 -11.1556 +1962 12 12 0 0.72 0.9553 -9.5389 -16.2278 +1962 12 13 0 0.713 0.9155 -3.2 -14.2444 +1962 12 14 0 0.707 0.9951 2.0167 -11.3778 +1962 12 15 0.02 0.701 1.0349 6.65 -12.75 +1962 12 16 0 0.696 1.1145 9.65 -5.5111 +1962 12 17 0 0.691 1.1344 12.5611 -5.5778 +1962 12 18 0 0.687 1.0648 17.1833 -3.1556 +1962 12 19 0 0.683 1.015 15.8056 -1.8222 +1962 12 20 0.02 0.679 1.015 14.7833 1.5556 +1962 12 21 4.03 0.676 1.025 10.1778 -1.3 +1962 12 22 1.2 0.674 1.025 9.2389 -2.4889 +1962 12 23 0.16 0.672 1.0449 8.0556 -5.4611 +1962 12 24 13.51 0.67 1.0051 3.95 -6.9444 +1962 12 25 13.33 0.669 1.1344 2.1889 -3.9778 +1962 12 26 0.43 0.669 1.7514 8.0556 -1.2889 +1962 12 27 0.1 0.668 1.7613 8.9 0.9389 +1962 12 28 0.09 0.669 1.5424 10.9722 0.6556 +1962 12 29 18.98 0.669 1.5922 7.6556 1.2556 +1962 12 30 0.04 0.671 2.239 5.2111 -4.1278 +1962 12 31 0 0.672 1.9106 2.6333 -8.0556 +1963 1 1 0 0.67 1.6021 6.1167 -9.2389 +1963 1 2 0 0.68 1.4727 8.9222 -8.1 +1963 1 3 0 0.683 1.3931 8.8611 -8.0944 +1963 1 4 0 0.687 1.3235 10.0889 -7.1167 +1963 1 5 0.02 0.692 1.2737 7.0167 -4.0278 +1963 1 6 0.01 0.697 1.2638 8.9111 -3.8667 +1963 1 7 0.03 0.702 1.2538 8.0278 -2.1056 +1963 1 8 0.09 0.708 1.224 5.8611 -1.0833 +1963 1 9 0.01 0.714 1.1742 13.7944 -7.4778 +1963 1 10 1.51 0.721 1.1145 11.9222 -1.6 +1963 1 11 27.79 0.728 1.1742 15.95 4.8833 +1963 1 12 0.87 0.735 2.0599 18.0722 7.0944 +1963 1 13 2.52 0.744 2.0698 11.6444 -1.9167 +1963 1 14 0 0.752 1.6519 0.5667 -10.95 +1963 1 15 0 0.761 1.4926 2.5222 -12.5778 +1963 1 16 0.02 0.77 1.413 7.7167 -11.9722 +1963 1 17 0.08 0.78 1.3434 7.6833 -10.0167 +1963 1 18 8.62 0.79 1.3931 9.1944 -3.0111 +1963 1 19 24.51 0.801 1.5822 9.0389 3.2556 +1963 1 20 4.4 0.812 2.647 15.1722 3.3444 +1963 1 21 0.1 0.823 2.6271 4.5833 -9.6778 +1963 1 22 0.24 0.835 2.0698 7.9889 -11.7944 +1963 1 23 2.71 0.848 1.8409 6.4889 -7.8778 +1963 1 24 0 0.86 1.5325 -2.3333 -14.6056 +1963 1 25 0.01 0.873 1.4628 2.2333 -15.2278 +1963 1 26 1.94 0.887 1.5126 5.4611 -8.5111 +1963 1 27 0.78 0.901 1.5524 2.0778 -7.5111 +1963 1 28 0.19 0.915 1.2439 0.5 -15.5444 +1963 1 29 0.05 0.93 1.1842 3.3222 -13.1889 +1963 1 30 3.67 0.945 1.3334 9.8722 -4.5278 +1963 1 31 0.01 0.961 1.3931 10.5 -1.0611 +1963 2 1 2.16 0.976 1.3334 5.7056 -1.0944 +1963 2 2 15.09 0.993 1.3235 7.2556 -1.35 +1963 2 3 2.87 1.009 1.8111 6.6 -3.1333 +1963 2 4 0.09 1.026 1.7912 6.3222 -9.1556 +1963 2 5 0.34 1.044 1.5623 13.7556 -5.8889 +1963 2 6 0 1.061 1.5026 17.6056 -3.2556 +1963 2 7 0 1.079 1.4329 14.6222 -2.2278 +1963 2 8 0 1.098 1.3832 9.1222 -1.8667 +1963 2 9 0.03 1.116 1.3334 5.3167 -4.5556 +1963 2 10 0.04 1.135 1.2837 10 -7.0111 +1963 2 11 9.95 1.155 1.2538 9.9389 -1.7222 +1963 2 12 10.62 1.174 1.5424 4.0056 -3.2722 +1963 2 13 0.01 1.194 1.7713 2.9222 -9.9556 +1963 2 14 0.07 1.215 1.5623 5.5556 -8.4611 +1963 2 15 0 1.235 1.3135 1.4667 -11.1611 +1963 2 16 0 1.256 1.2439 2.3333 -13.4722 +1963 2 17 0 1.277 1.1941 6.25 -12.8611 +1963 2 18 0.08 1.299 1.224 9.9111 -10.4556 +1963 2 19 16.38 1.321 1.2936 6.0944 -3.4667 +1963 2 20 0 1.343 1.4329 11.25 -2.7722 +1963 2 21 0.01 1.365 1.5026 8.2556 -4.3278 +1963 2 22 0 1.387 1.3832 0.2722 -16.1778 +1963 2 23 0 1.41 1.3434 5.4 -13.2167 +1963 2 24 0.39 1.433 1.3235 8.2111 -6.2278 +1963 2 25 0.2 1.457 1.2737 15.5 -6.3389 +1963 2 26 1.52 1.48 1.2339 9.1278 -5.1 +1963 2 27 0.03 1.504 1.1941 5.3 -14.2278 +1963 2 28 1.28 1.528 1.214 12.1556 -6.8278 +1963 3 1 19.5 1.552 1.2538 9.8056 0.8278 +1963 3 2 0.26 1.576 1.9504 10.1389 -0.2722 +1963 3 3 0.06 1.601 1.821 15.0167 -5.1778 +1963 3 4 4.23 1.626 1.632 16.3556 -1.2944 +1963 3 5 75.65 1.651 1.9404 15.6333 8.4611 +1963 3 6 8.16 1.676 10.5481 12.0722 3.5444 +1963 3 7 0 1.701 8.4782 11.1333 -1.1944 +1963 3 8 0 1.726 5.9407 14.3167 -3.2167 +1963 3 9 0.17 1.752 3.3236 13.9 -1.7111 +1963 3 10 0.28 1.778 2.6967 14.55 0.1611 +1963 3 11 32.9 1.803 2.5773 12.9444 -0.7833 +1963 3 12 83.5 1.829 8.9758 14.15 5.5167 +1963 3 13 0.13 1.856 14.3294 22.1944 4.9889 +1963 3 14 0.02 1.882 9.7619 19.9944 3.0944 +1963 3 15 0.07 1.908 7.5827 14.1389 -2.2722 +1963 3 16 2.49 1.935 4.8362 12.9222 2.7778 +1963 3 17 9.58 1.961 3.7117 23.5111 6.85 +1963 3 18 0.56 1.988 3.4231 24.7889 7.2056 +1963 3 19 19.07 2.014 3.0649 23.4889 9.5889 +1963 3 20 2.98 2.041 4.1197 16.4778 5.4333 +1963 3 21 0.06 2.068 3.5824 7.1444 -1.3278 +1963 3 22 0.03 2.095 3.0351 8.3278 -3.1444 +1963 3 23 0 2.122 2.7465 16.1278 -4.5444 +1963 3 24 0 2.149 2.5873 20.5889 -1.9389 +1963 3 25 0.1 2.176 2.438 20.5 1.0833 +1963 3 26 2.06 2.203 2.3484 18.4778 7.3611 +1963 3 27 0.04 2.23 2.3285 19.15 5.6 +1963 3 28 0 2.257 2.1594 21.0444 3.0167 +1963 3 29 0 2.283 2.0698 23.8333 0.5722 +1963 3 30 0 2.31 1.9902 25.2556 2.15 +1963 3 31 0 2.337 1.9504 26.0667 4.0611 +1963 4 1 0 2.364 1.8807 25.1 6.7556 +1963 4 2 0 2.391 1.8111 26.6222 6.6111 +1963 4 3 0 2.418 1.7713 28.3056 7.4667 +1963 4 4 0.01 2.445 1.7514 24.1056 10.5722 +1963 4 5 0 2.472 1.7116 17.0778 1.5722 +1963 4 6 10.41 2.498 1.6917 10.7389 4.2833 +1963 4 7 9.32 2.525 1.9802 18.1889 4.7833 +1963 4 8 0.07 2.551 1.8907 21.2056 0.8556 +1963 4 9 0.38 2.578 1.7215 21.6 6.6722 +1963 4 10 0.04 2.604 1.6519 19.3833 5.6556 +1963 4 11 0.1 2.63 1.5822 19.1389 5.0944 +1963 4 12 0 2.656 1.5424 19.5444 6.0556 +1963 4 13 0.04 2.682 1.4926 16.1444 1.1 +1963 4 14 0.01 2.708 1.4528 12.9222 2.5611 +1963 4 15 0 2.734 1.423 15.4778 -0.2167 +1963 4 16 0 2.759 1.413 19.9111 -2.4889 +1963 4 17 0 2.785 1.3931 26.9889 7.0667 +1963 4 18 0 2.81 1.3633 27.3 8.8667 +1963 4 19 0.03 2.835 1.3135 26.4278 9.8833 +1963 4 20 0.2 2.86 1.2737 26.3222 12.7111 +1963 4 21 0.03 2.885 1.2339 29.0556 5.2444 +1963 4 22 0.04 2.909 1.224 29.25 9.95 +1963 4 23 0.39 2.934 1.214 26.2444 13.0611 +1963 4 24 0 2.958 1.1643 19.2278 1.9611 +1963 4 25 0 2.982 1.1543 16.55 3.4722 +1963 4 26 0 3.005 1.1742 20.1778 2.75 +1963 4 27 0 3.029 1.2041 20.5889 2.1722 +1963 4 28 21.25 3.052 1.2638 15.85 8.2833 +1963 4 29 60.12 3.075 1.8807 13.6722 10.1 +1963 4 30 16.04 3.098 4.9058 19.8111 9.2278 +1963 5 1 0.03 3.12 4.6869 15.0944 1.4889 +1963 5 2 0 3.143 3.1246 20.8222 -1.8611 +1963 5 3 0 3.165 2.3783 22.15 1.4944 +1963 5 4 0 3.186 2.0897 24.5333 2.3556 +1963 5 5 0.03 3.208 1.9205 25.6722 4.9833 +1963 5 6 0.37 3.229 1.7912 26.5611 9.6833 +1963 5 7 0 3.25 1.6718 26.0889 8.3278 +1963 5 8 0 3.27 1.632 27.5667 11.3889 +1963 5 9 0 3.29 1.5524 29.1444 10.3944 +1963 5 10 0.38 3.31 1.4926 29.0556 10.9722 +1963 5 11 0.97 3.33 1.4329 28.75 15.2056 +1963 5 12 0.09 3.349 1.3732 24.4611 11.6611 +1963 5 13 3.08 3.368 1.3434 18.4333 10.2222 +1963 5 14 0.46 3.387 1.3633 24.95 10.95 +1963 5 15 1.05 3.405 1.3633 27.8222 9.9556 +1963 5 16 5.69 3.423 1.3732 27.4222 12.15 +1963 5 17 5.66 3.441 1.2837 26.5944 14.8278 +1963 5 18 0 3.458 1.2737 23.3778 12.3444 +1963 5 19 0 3.475 1.2339 25.5278 7.3944 +1963 5 20 0.74 3.492 1.1543 24.7722 10.6444 +1963 5 21 0.84 3.508 1.1742 24.55 10.8889 +1963 5 22 0.67 3.523 1.1643 24.0722 8.0889 +1963 5 23 0.14 3.539 1.1344 20.3722 7.7 +1963 5 24 0 3.554 1.0747 19.3667 3.4611 +1963 5 25 3.58 3.569 1.0349 15.9056 8.7444 +1963 5 26 11.45 3.583 1.1742 15.7056 10.0667 +1963 5 27 24.9 3.597 1.3633 16.75 11.8389 +1963 5 28 13.26 3.61 1.8807 23.5722 13.1889 +1963 5 29 4.86 3.623 2.1693 25.3611 14.7667 +1963 5 30 0.22 3.636 1.8011 24.7667 12.5556 +1963 5 31 0.21 3.648 1.4329 24.1778 10.8944 +1963 6 1 0 3.66 1.2737 23.4611 9.6167 +1963 6 2 0 3.671 1.1643 24.8667 7.4778 +1963 6 3 0.08 3.682 1.1145 25.5556 8.3889 +1963 6 4 0.02 3.693 1.0648 22.6556 11.45 +1963 6 5 0.76 3.703 1.0648 24.9389 11.3889 +1963 6 6 2.45 3.713 1.0449 25.6444 12.3556 +1963 6 7 1.29 3.722 1.0747 29.1167 13.1556 +1963 6 8 0.36 3.731 1.0747 29.5944 14.7056 +1963 6 9 0.14 3.739 1.025 31.2833 14.2222 +1963 6 10 5.99 3.747 0.9911 31.8611 14.9722 +1963 6 11 0.13 3.755 1.1145 29.4722 15.7444 +1963 6 12 0.09 3.762 0.9802 26.4056 14.0389 +1963 6 13 0 3.768 0.9036 27.6056 12.35 +1963 6 14 9.38 3.774 0.9583 28.1 14.8444 +1963 6 15 0 3.78 0.9145 27.9556 13.0167 +1963 6 16 12.55 3.785 0.8926 23.0833 13.8833 +1963 6 17 11.64 3.79 1.0946 19.2389 14.5722 +1963 6 18 2.25 3.795 1.214 19.5333 14.0556 +1963 6 19 1.46 3.798 1.1046 23.7278 14.5556 +1963 6 20 15.16 3.802 1.0747 24.9556 15.9278 +1963 6 21 4.71 3.805 1.3732 24.1056 16.25 +1963 6 22 5.39 3.807 1.6817 21.5889 14.8944 +1963 6 23 1.45 3.809 1.7215 21.4722 14.3222 +1963 6 24 0.11 3.811 1.3135 24.4667 13.9056 +1963 6 25 0.27 3.812 1.1643 25.4667 12.7333 +1963 6 26 19.42 3.813 1.0946 23.0722 13.9222 +1963 6 27 27.18 3.813 1.9703 23.4 16.2 +1963 6 28 3.61 3.813 3.4132 26.2111 15.8111 +1963 6 29 7.98 3.812 2.4081 25.7944 14.8333 +1963 6 30 2.71 3.811 1.9504 26.4944 15.6222 +1963 7 1 2.33 3.809 2.1395 28.1167 15.6222 +1963 7 2 1.5 3.807 1.821 28.1833 16.3111 +1963 7 3 0.01 3.804 1.5723 28.7222 16.6111 +1963 7 4 0 3.801 1.3434 27.25 13.2222 +1963 7 5 0.1 3.798 1.2041 27.9444 12.6889 +1963 7 6 6.59 3.794 1.1145 28.0222 10.5944 +1963 7 7 10.39 3.789 1.2339 24.0444 14.6333 +1963 7 8 2.83 3.785 1.2936 27.3667 15.7556 +1963 7 9 2.22 3.779 1.1245 25.0833 14.1944 +1963 7 10 0.06 3.773 1.015 22.7278 9.6722 +1963 7 11 0.07 3.767 0.9822 24.4833 7.6944 +1963 7 12 0.58 3.76 0.9016 25.2667 9.2889 +1963 7 13 6.45 3.753 0.8906 25.5611 11.9722 +1963 7 14 5.9 3.746 0.9135 26.5167 14.6333 +1963 7 15 0.35 3.738 0.9364 27.6278 14.4556 +1963 7 16 7.73 3.729 0.9135 25.4 14.9222 +1963 7 17 11.63 3.72 0.9364 27.7611 16.9778 +1963 7 18 7.6 3.711 1.3334 28.5611 16.2944 +1963 7 19 1.74 3.701 1.5325 28.2444 17.0444 +1963 7 20 14.78 3.691 1.1046 27.7056 16.9333 +1963 7 21 0.64 3.68 1.224 25.5056 15.2889 +1963 7 22 0.7 3.669 1.1643 27.1722 12.6667 +1963 7 23 12.87 3.658 1.025 25.6 14.15 +1963 7 24 0.53 3.646 1.3135 22.6944 14.7 +1963 7 25 19.66 3.634 1.3135 24.5556 16.2722 +1963 7 26 0.02 3.621 1.8111 28.1722 15.3944 +1963 7 27 4.53 3.608 1.4329 29.4333 15.1667 +1963 7 28 4.89 3.594 1.2936 29.4222 16.3444 +1963 7 29 9.04 3.58 1.3135 28.1 15.4167 +1963 7 30 6.56 3.566 1.5623 27.1111 16.3556 +1963 7 31 0.24 3.551 1.4329 27.6333 16.8833 +1963 8 1 1.26 3.536 1.2439 28.8333 15.1722 +1963 8 2 0.02 3.521 1.0747 29.2611 14.6111 +1963 8 3 0.12 3.505 0.9593 31.2833 13.7833 +1963 8 4 0.65 3.489 0.8687 30.8778 15.2333 +1963 8 5 0 3.472 0.8359 29.8 16.6778 +1963 8 6 0.03 3.455 0.803 31.0889 15.0056 +1963 8 7 0.97 3.438 0.7812 31.3222 15.9889 +1963 8 8 1.39 3.42 0.8468 29.4278 16.6944 +1963 8 9 0.13 3.402 0.7613 29.6056 12.5056 +1963 8 10 11.58 3.384 0.7812 24.8833 13.8056 +1963 8 11 0.04 3.365 0.8578 26.0833 12.7167 +1963 8 12 0.17 3.346 0.7812 28.0722 11.7111 +1963 8 13 4.71 3.327 0.7214 27.4889 14.8611 +1963 8 14 0 3.307 0.7314 24.0389 13.6111 +1963 8 15 0 3.287 0.7214 25.6778 8.5889 +1963 8 16 0.02 3.267 0.6816 26.3389 11.0056 +1963 8 17 0.04 3.246 0.6528 27.9556 12.4278 +1963 8 18 4.82 3.225 0.6727 29.3556 13.2611 +1963 8 19 3.06 3.204 0.6438 27.6333 14.5833 +1963 8 20 0.56 3.182 0.6916 27.7667 15.1667 +1963 8 21 6.82 3.161 0.9254 26.3611 16.1 +1963 8 22 6.44 3.139 0.7712 28.1722 14.95 +1963 8 23 0.1 3.116 0.7314 29.0833 13.6222 +1963 8 24 0.18 3.094 0.7115 29.4333 13.6056 +1963 8 25 14.02 3.071 0.6627 28.25 15.3611 +1963 8 26 2.44 3.048 0.7513 24.1444 16.0667 +1963 8 27 0.9 3.025 0.9593 23.6833 14.8444 +1963 8 28 0.34 3.001 0.814 25.5556 15.45 +1963 8 29 20.05 2.977 0.7712 26.5556 16.0444 +1963 8 30 0.16 2.954 1.1046 26.8167 17.1444 +1963 8 31 0 2.929 0.8249 26.3278 13.0444 +1963 9 1 0 2.905 0.7214 25.8444 11.0722 +1963 9 2 0 2.88 0.6349 25.7333 11.9778 +1963 9 3 0.01 2.856 0.6528 28.0333 12.5667 +1963 9 4 5.44 2.831 0.7115 26.3 15.1722 +1963 9 5 1.87 2.806 0.7712 27.1667 15.9944 +1963 9 6 2.07 2.78 0.7413 23.5278 15.4611 +1963 9 7 1.65 2.755 0.7015 24.9722 14.3833 +1963 9 8 0.1 2.729 0.7413 26.8278 13.7222 +1963 9 9 0 2.704 0.7921 27.4 11.4278 +1963 9 10 0.05 2.678 0.6438 27.8 11.3889 +1963 9 11 0.1 2.652 0.5971 27.7333 13.3167 +1963 9 12 6.4 2.626 0.6249 27.9444 14.0333 +1963 9 13 1.67 2.599 0.7214 23.9056 15.2833 +1963 9 14 3.54 2.573 0.6349 19.3556 11.8389 +1963 9 15 0.41 2.547 0.6349 20.0389 10.8444 +1963 9 16 0.02 2.52 0.615 24.8611 11.6333 +1963 9 17 0.16 2.494 0.5692 26.3389 10.6889 +1963 9 18 0 2.467 0.615 24.5722 10.55 +1963 9 19 0 2.44 0.5871 26.9611 8.85 +1963 9 20 0 2.413 0.5782 28.1444 8.7889 +1963 9 21 0 2.386 0.5513 28.8056 9.9111 +1963 9 22 0 2.36 0.5423 24.3889 11.3389 +1963 9 23 0 2.333 0.5244 19.9389 4.1389 +1963 9 24 0.02 2.306 0.4816 17.7722 1.6278 +1963 9 25 0.45 2.279 0.4737 20.5389 3.1944 +1963 9 26 0.46 2.252 0.4896 23.4944 10.1833 +1963 9 27 0.58 2.225 0.4816 23.6222 9.5278 +1963 9 28 83.86 2.198 0.7642 18.4611 10.3389 +1963 9 29 0.27 2.171 3.3037 21.4444 10.5833 +1963 9 30 0.04 2.144 2.0599 21.0111 9.1667 +1963 10 1 0 2.117 1.1344 20.5889 3.9278 +1963 10 2 0 2.09 0.9364 22.9 3.3778 +1963 10 3 0 2.063 0.8578 25.6111 6.7778 +1963 10 4 0 2.036 0.7413 24.2056 7.1944 +1963 10 5 0 2.01 0.6727 22.5 4.7722 +1963 10 6 0 1.983 0.6438 23.8778 4.1889 +1963 10 7 0 1.956 0.606 25.1722 4.4 +1963 10 8 0 1.93 0.615 24.8167 5.3611 +1963 10 9 0 1.903 0.6249 22.4722 7.3 +1963 10 10 0 1.877 0.615 21.0389 3.3889 +1963 10 11 0.08 1.851 0.5871 23.7278 3.1889 +1963 10 12 1.12 1.825 0.5871 24.7333 7.3056 +1963 10 13 0 1.799 0.5782 21.3 6.5278 +1963 10 14 0 1.773 0.5692 21.6833 3.1556 +1963 10 15 0 1.747 0.5513 22.5833 2.8 +1963 10 16 0 1.722 0.5692 24.1556 0.9611 +1963 10 17 0 1.696 0.5692 24.9278 0.0944 +1963 10 18 0 1.671 0.5602 24.3111 1.4111 +1963 10 19 0 1.646 0.5423 24.5333 3.1667 +1963 10 20 0 1.621 0.5423 24.7444 4.5611 +1963 10 21 0 1.596 0.4975 25.5222 6.3556 +1963 10 22 0.33 1.572 0.5244 23.7333 5.5389 +1963 10 23 0.34 1.548 0.5513 20.3611 10.5389 +1963 10 24 0.24 1.523 0.5513 22.2667 10.5444 +1963 10 25 0.02 1.5 0.5782 23.1333 10.3778 +1963 10 26 0 1.476 0.5513 25.3167 7.75 +1963 10 27 0 1.452 0.5423 24.8611 7.3389 +1963 10 28 0.43 1.429 0.5155 22.2167 8.2111 +1963 10 29 0.03 1.406 0.5065 14.6444 2.5611 +1963 10 30 0 1.383 0.5334 14 -1.2944 +1963 10 31 0.27 1.361 0.5155 20.25 -2.9111 +1963 11 1 14.1 1.339 0.5423 15.4833 2.6611 +1963 11 2 0 1.317 0.6349 8.3389 -1.7556 +1963 11 3 0 1.295 0.606 11.9333 -5.6278 +1963 11 4 0 1.274 0.5244 15.3167 -4.5333 +1963 11 5 20.79 1.252 0.5244 13.65 3.3667 +1963 11 6 4.7 1.232 0.9364 15.7 8.2611 +1963 11 7 0.06 1.211 1.1742 14.6 7.8722 +1963 11 8 0 1.191 0.7613 15.2944 2.5833 +1963 11 9 0 1.171 0.6438 17.2056 -1.0778 +1963 11 10 0 1.151 0.615 20.0722 2.0667 +1963 11 11 0 1.132 0.5602 17.4611 1.2333 +1963 11 12 0 1.113 0.5513 13.1167 -0.8611 +1963 11 13 0.07 1.094 0.5782 7.8222 -5.5667 +1963 11 14 0.15 1.076 0.5602 4.0222 -4.1389 +1963 11 15 0 1.058 0.5513 10.8 -5.2056 +1963 11 16 0 1.04 0.5513 16.5833 -6.3222 +1963 11 17 0.02 1.023 0.5423 20.0056 -3.5389 +1963 11 18 0.02 1.006 0.5155 20.2778 -1.0111 +1963 11 19 0.05 0.99 0.5334 20.45 3.9167 +1963 11 20 0.77 0.974 0.5602 16.4 3.8611 +1963 11 21 0.54 0.958 0.5782 17.6333 6.7222 +1963 11 22 1.31 0.942 0.5871 18.2778 8.6111 +1963 11 23 14.07 0.927 0.606 17.6889 9.7 +1963 11 24 0.17 0.913 0.7613 14.4944 -0.4056 +1963 11 25 0.02 0.898 0.803 11.2833 -3.7278 +1963 11 26 11.9 0.885 0.6816 9.6889 -0.0833 +1963 11 27 1.21 0.871 0.7513 17.3833 5.7167 +1963 11 28 19.3 0.858 0.8578 16.6111 9.0556 +1963 11 29 57.86 0.845 3.6122 12.2611 -0.0611 +1963 11 30 0.38 0.833 5.0253 2.7167 -5.2167 +1963 12 1 0.08 0.821 3.1843 3.9667 -5.1389 +1963 12 2 1.11 0.81 1.8409 6.7444 -6.0333 +1963 12 3 0.34 0.799 1.5325 3.6111 -3.8944 +1963 12 4 0 0.788 1.3235 7.0167 -8.4222 +1963 12 5 0.02 0.778 1.2041 4.1389 -5.9333 +1963 12 6 0 0.769 1.1245 9.0944 -6.4333 +1963 12 7 0.04 0.759 1.0548 11.95 -6.4222 +1963 12 8 4.51 0.75 1.025 7.3667 -4.1778 +1963 12 9 0.03 0.742 1.0449 3.5278 -3.7667 +1963 12 10 0.02 0.734 1.0349 8.1056 -5.8389 +1963 12 11 18.7 0.727 1.025 5.8833 -2.8667 +1963 12 12 3.11 0.72 1.3633 10.5944 1.0167 +1963 12 13 3.86 0.713 1.6519 7.5722 1.8278 +1963 12 14 7.21 0.707 1.4628 3.9167 -3.85 +1963 12 15 0.17 0.701 1.4628 -1.4556 -12.5833 +1963 12 16 0 0.696 1.2439 -1.8944 -13.2278 +1963 12 17 0.06 0.691 1.1046 1.75 -13.6389 +1963 12 18 0.12 0.687 1.0747 1.6056 -11.2556 +1963 12 19 0 0.683 1.0349 0.5667 -15.3167 +1963 12 20 0 0.679 0.9951 -0.85 -12.1833 +1963 12 21 0.04 0.676 0.9951 1.5056 -12.2333 +1963 12 22 0.27 0.674 0.9951 3.4111 -10.3389 +1963 12 23 22.9 0.672 0.9055 1.4667 -6.5389 +1963 12 24 0.03 0.67 0.9951 1.3722 -7.0444 +1963 12 25 0 0.669 0.9603 8.2833 -8.2111 +1963 12 26 0 0.669 0.9165 14.05 -6.3667 +1963 12 27 0 0.668 0.9931 9.8667 -3.3222 +1963 12 28 0 0.669 1.0747 5.75 -4.4444 +1963 12 29 0 0.669 1.0051 4.5722 -6.4111 +1963 12 30 0.31 0.671 0.9384 3.6833 -9.0778 +1963 12 31 32.97 0.672 0.9055 1.2722 -7.9833 +1964 1 1 9.01 0.67 1.1643 2.2167 -4.55 +1964 1 2 0 0.68 1.6718 8.9444 -7.9333 +1964 1 3 0 0.683 1.3036 14.5556 -5.1722 +1964 1 4 0 0.687 1.4329 10.5556 -1.2778 +1964 1 5 0.03 0.692 1.632 10.95 -6.9722 +1964 1 6 6.19 0.697 1.4926 9.3722 -4.0611 +1964 1 7 1 0.702 1.9305 10.5278 2.5222 +1964 1 8 10.48 0.708 2.4877 7.7 1.3389 +1964 1 9 17.95 0.714 3.9406 12.35 0.8722 +1964 1 10 0.22 0.721 4.8959 6.3778 -7.7722 +1964 1 11 0.08 0.728 3.3037 6.2889 -11.2056 +1964 1 12 14.77 0.735 2.438 3.3556 -4.5889 +1964 1 13 1.2 0.744 2.6072 -1.15 -8.5722 +1964 1 14 0.1 0.752 2.0698 -2.2278 -12.9556 +1964 1 15 0 0.761 1.5723 2.8 -15.5722 +1964 1 16 0 0.77 1.5026 3.9944 -13.1778 +1964 1 17 0 0.78 1.4926 6.9333 -6.9222 +1964 1 18 0 0.79 1.5723 11.5944 -3.8667 +1964 1 19 0.62 0.801 1.5026 10.5556 -3.8278 +1964 1 20 13.13 0.812 1.8111 8.9111 -0.1333 +1964 1 21 0 0.823 2.1693 13.9667 -2.2056 +1964 1 22 0 0.835 1.8111 17.2444 -4.3556 +1964 1 23 0.54 0.848 1.6718 18.7222 -1.0667 +1964 1 24 49.3 0.86 1.6917 14.1889 1.9222 +1964 1 25 9.83 0.873 6.2592 11.8889 1.7611 +1964 1 26 0 0.887 6.2791 12.7722 -2.7778 +1964 1 27 0 0.901 4.7267 12.9167 -3.1056 +1964 1 28 0 0.915 2.9156 7.6611 -4.5278 +1964 1 29 0 0.93 2.4081 8.1111 -11.7778 +1964 1 30 0.07 0.945 2.1494 12.9611 -7.3444 +1964 1 31 4.74 0.961 2.0101 9.6833 -2.4833 +1964 2 1 0.26 0.976 2.0002 9.8556 0.9278 +1964 2 2 0 0.993 1.9205 10.0667 -2.3167 +1964 2 3 0 1.009 1.7514 10.5444 -6.9611 +1964 2 4 0.34 1.026 1.6618 12.8944 -7.4389 +1964 2 5 29.17 1.044 1.622 11.4722 -6.0944 +1964 2 6 3.79 1.061 3.045 8.6444 -0.9944 +1964 2 7 0.06 1.079 3.2938 10.0278 0.1222 +1964 2 8 0.03 1.098 2.438 4.9222 -6.6778 +1964 2 9 1.91 1.116 2.1295 7.1833 -8.1056 +1964 2 10 4.21 1.135 2.0002 8.3333 -5.9778 +1964 2 11 0.33 1.155 1.9504 4.0833 -4.9333 +1964 2 12 0.25 1.174 1.8011 6.4833 -10.8778 +1964 2 13 5.3 1.194 1.7116 5.4833 -3.1556 +1964 2 14 0.78 1.215 1.7514 8.0944 -3.7111 +1964 2 15 22.5 1.235 1.7613 5.2667 -4.3167 +1964 2 16 0.15 1.256 2.6171 4.5167 -2.7 +1964 2 17 0 1.277 2.4081 9.4 -8.5444 +1964 2 18 24.53 1.299 2.4181 6.5389 -2.6056 +1964 2 19 1.85 1.321 3.2938 4.9444 -1.6722 +1964 2 20 1.95 1.343 2.7465 2.6389 -3.5 +1964 2 21 0.09 1.365 2.3484 2.0333 -5.4611 +1964 2 22 0 1.387 2.1395 0.1611 -7.5944 +1964 2 23 0 1.41 1.9703 4.3944 -12 +1964 2 24 0.12 1.433 1.8708 9.8167 -9.5778 +1964 2 25 13.93 1.457 1.8509 6.4 -5.25 +1964 2 26 0.04 1.48 1.9106 9.75 -4.9667 +1964 2 27 0.12 1.504 1.9603 6.9278 -2.8722 +1964 2 28 10.05 1.528 1.9305 2.6889 -2.5444 +1964 2 29 0.05 1.552 1.9205 7.5389 -7.2722 +1964 3 1 0.54 1.576 1.8807 8.2833 -2.1833 +1964 3 2 25.18 1.601 1.9703 9.5222 1.2444 +1964 3 3 0.71 1.626 3.9207 18.9889 4.4944 +1964 3 4 16.6 1.651 3.7515 20.5556 5.95 +1964 3 5 16.25 1.676 6.3587 18 4.75 +1964 3 6 0.02 1.701 6.0104 14.3722 -3.4278 +1964 3 7 1.29 1.726 4.3088 14.9944 1.0333 +1964 3 8 0.01 1.752 3.2838 20.9833 4.2889 +1964 3 9 3.81 1.778 2.9256 19.6056 10.4167 +1964 3 10 13.51 1.803 3.443 16.3556 4.3167 +1964 3 11 0.02 1.829 3.851 15.3444 -3.5778 +1964 3 12 0 1.856 3.1246 15.3111 -1.9333 +1964 3 13 0 1.882 2.7664 14.8556 -4.3278 +1964 3 14 32.97 1.908 2.5674 12.8056 2.1778 +1964 3 15 13.29 1.935 4.3983 12.9778 4.4278 +1964 3 16 0 1.961 4.7367 15.35 -3.3722 +1964 3 17 0 1.988 3.7714 16.7944 -2.2944 +1964 3 18 0 2.014 3.1943 13.1167 0.0056 +1964 3 19 7.42 2.041 2.846 12.1611 -5.1944 +1964 3 20 4.16 2.068 2.8261 8.5667 0.2222 +1964 3 21 8.45 2.095 3.045 7.7111 0.4278 +1964 3 22 0 2.122 2.8858 10.9333 -1.45 +1964 3 23 0.01 2.149 2.5972 14.8722 -3.2222 +1964 3 24 0.07 2.176 2.4579 16.4 -0.3722 +1964 3 25 20.33 2.203 2.3982 14.7111 5.5056 +1964 3 26 25.26 2.23 4.7864 15 6.5278 +1964 3 27 0 2.257 4.8859 13.5333 -3.0167 +1964 3 28 0 2.283 3.7217 16.5444 -1.9333 +1964 3 29 0.12 2.31 3.1346 12.8389 -0.0722 +1964 3 30 0.36 2.337 2.836 5.7056 -9.3889 +1964 3 31 0.01 2.364 2.647 10.5722 -9.0389 +1964 4 1 0.25 2.391 2.4977 13.8944 -3.0389 +1964 4 2 0.04 2.418 2.3584 18.6611 0.8333 +1964 4 3 0.6 2.445 2.2788 19.2444 7.9111 +1964 4 4 14.58 2.472 2.2489 14.7333 5.8722 +1964 4 5 1.4 2.498 2.3982 9.2667 2.9556 +1964 4 6 37.81 2.525 3.1147 14.4444 4.5111 +1964 4 7 48.42 2.551 8.5579 20.0333 9.2167 +1964 4 8 8.92 2.578 9.5231 17.8 6.7444 +1964 4 9 0 2.604 6.8463 12.0556 -1.6556 +1964 4 10 0 2.63 5.6522 16.3111 -2.7778 +1964 4 11 0 2.656 4.1396 19.2667 -0.85 +1964 4 12 1.84 2.682 3.6321 16.7111 3.45 +1964 4 13 21.46 2.708 3.5326 15.0111 8.3556 +1964 4 14 0.01 2.734 4.4282 18.5333 9.6889 +1964 4 15 0 2.759 4.0103 18.3 6.3278 +1964 4 16 0 2.785 3.4828 21.7611 0.7444 +1964 4 17 0 2.81 3.2241 24.5333 4.0722 +1964 4 18 0.41 2.835 3.045 25.6389 8.6444 +1964 4 19 0 2.86 2.9256 27.4222 7.9833 +1964 4 20 0.02 2.885 2.7763 27.1889 10.55 +1964 4 21 0 2.909 2.6569 27.3611 9.8944 +1964 4 22 0.27 2.934 2.5574 24.7556 11.4944 +1964 4 23 13.01 2.958 2.5375 23.6833 11.6778 +1964 4 24 0.75 2.982 2.7763 24.1444 10.8667 +1964 4 25 7.95 3.005 2.5972 18.3 10.2833 +1964 4 26 16.51 3.029 2.5873 11.4111 6.6444 +1964 4 27 32.95 3.052 4.07 14.2222 6.0389 +1964 4 28 16.04 3.075 6.1497 21.6444 9.2167 +1964 4 29 0.09 3.098 6.6274 21.9278 7.9333 +1964 4 30 0 3.12 6.0104 21.7278 4.9722 +1964 5 1 0.01 3.143 4.5078 20.9389 4.9167 +1964 5 2 23.38 3.165 3.5824 15.1333 7.9333 +1964 5 3 4.6 3.186 4.8163 17.0722 7.9444 +1964 5 4 0 3.208 4.6272 22.4278 6.4278 +1964 5 5 0 3.229 3.851 24.3167 6.0389 +1964 5 6 0 3.25 3.3933 23.7278 7.8111 +1964 5 7 0 3.27 3.1644 25.75 7.7889 +1964 5 8 0 3.29 3.0052 28.8389 8.6111 +1964 5 9 0 3.31 2.8261 27.1056 10.85 +1964 5 10 0 3.33 2.6669 26.8833 9.1444 +1964 5 11 1.63 3.349 2.5276 25.1611 10.5889 +1964 5 12 7.15 3.368 2.5276 23.5889 13.4 +1964 5 13 1.85 3.387 2.5972 24.0389 13.6111 +1964 5 14 0.04 3.405 2.3982 18.9111 7.2833 +1964 5 15 0.01 3.423 2.2887 23.1889 5.05 +1964 5 16 0 3.441 2.1793 25.0722 4.8167 +1964 5 17 0 3.458 2.1096 27.3444 6.0444 +1964 5 18 0 3.475 2.04 27.55 9.5833 +1964 5 19 0.55 3.492 1.9504 28.6111 8.1 +1964 5 20 2.36 3.508 1.9006 28.9889 10.4056 +1964 5 21 1.8 3.523 1.8509 26.7833 10.8944 +1964 5 22 0.76 3.539 1.8509 27.5611 13.5 +1964 5 23 0.72 3.554 1.8608 27.7833 12.4611 +1964 5 24 2.49 3.569 1.7912 26.0222 13.0222 +1964 5 25 0.02 3.583 1.7912 28.0444 13.45 +1964 5 26 0.01 3.597 1.6917 28.6889 9.7667 +1964 5 27 0.31 3.61 1.622 29.0778 12.7333 +1964 5 28 0.51 3.623 1.6021 28.1889 14.9889 +1964 5 29 1.91 3.636 1.5723 20.1111 11.2778 +1964 5 30 0.01 3.648 1.6121 19.0833 6.5778 +1964 5 31 0.67 3.66 1.5524 23.0944 9.2833 +1964 6 1 18.68 3.671 1.5126 21.7389 12.8722 +1964 6 2 0.03 3.682 1.7414 22.4389 11.8167 +1964 6 3 0.03 3.693 1.5723 22.5389 7.7222 +1964 6 4 0 3.703 1.423 22.7389 7.3444 +1964 6 5 0.31 3.713 1.4429 25.2444 9.0278 +1964 6 6 3.82 3.722 1.4429 24.55 13.6222 +1964 6 7 5.92 3.731 1.5126 24.6 13.9111 +1964 6 8 0.05 3.739 1.4827 28.3056 12.8444 +1964 6 9 0.01 3.747 1.3931 30.6556 13.5556 +1964 6 10 0.01 3.755 1.3334 31.3389 15.3611 +1964 6 11 0.17 3.762 1.2936 31.5889 16.0333 +1964 6 12 3.84 3.768 1.2041 29.0278 17.0278 +1964 6 13 9.44 3.774 1.3235 28.8278 16.6611 +1964 6 14 0.05 3.78 1.3334 30.7944 15.7778 +1964 6 15 6.4 3.785 1.1742 30.9333 14.85 +1964 6 16 0.02 3.79 1.2339 28.5333 16.8611 +1964 6 17 0 3.795 1.1543 27.0111 14 +1964 6 18 0.67 3.798 1.0946 29.2889 15.9667 +1964 6 19 0.04 3.802 1.0946 31.0111 16.8278 +1964 6 20 0.59 3.805 1.0449 31.8556 15.9111 +1964 6 21 2 3.807 1.025 33.2667 16.2889 +1964 6 22 9.74 3.809 1.0648 33.3778 17.4278 +1964 6 23 8.02 3.811 1.4628 30.4 16.85 +1964 6 24 5.01 3.812 1.5026 27.1333 17.5278 +1964 6 25 0.27 3.813 1.3533 27.6111 16.0889 +1964 6 26 0.96 3.813 1.3334 24.4167 14.2778 +1964 6 27 0 3.813 1.1742 28.6722 12.95 +1964 6 28 0 3.812 1.0449 29.6 12.6278 +1964 6 29 0 3.811 0.9782 27.9667 12.7556 +1964 6 30 0.08 3.809 0.9254 28.1778 10.6056 +1964 7 1 1.44 3.807 0.9055 25.6944 14.05 +1964 7 2 8.08 3.804 0.9155 27.3889 14.0611 +1964 7 3 5.25 3.801 0.9563 27.35 16.3389 +1964 7 4 0.06 3.798 1.1543 26.7667 16.3611 +1964 7 5 0 3.794 1.0349 26.6667 11.0889 +1964 7 6 0.04 3.789 0.8757 27.9444 8.7611 +1964 7 7 0.03 3.785 0.8259 29.8667 13.8389 +1964 7 8 2.87 3.779 0.7961 28.7 16.3 +1964 7 9 3.79 3.773 0.8259 28.1556 16.2944 +1964 7 10 5.28 3.767 0.8558 28.0722 14.45 +1964 7 11 5.13 3.76 0.9055 27.7 14.0889 +1964 7 12 7.88 3.753 0.9891 24.3778 15.5778 +1964 7 13 5.39 3.746 0.9473 24.1278 16.2389 +1964 7 14 0 3.738 1.0747 26.7056 12.7444 +1964 7 15 5.34 3.729 0.9473 27.5667 10.8889 +1964 7 16 2.77 3.72 0.9016 27.0444 14.25 +1964 7 17 4 3.711 1.015 27.0722 14.2667 +1964 7 18 54.91 3.701 0.9016 22.1333 15.6667 +1964 7 19 24.78 3.691 3.7913 26.0556 16.6111 +1964 7 20 0.89 3.68 4.0998 25.9722 16.1944 +1964 7 21 10.99 3.669 2.5873 26.0167 17.0778 +1964 7 22 16.56 3.658 1.9802 27.5 17.1278 +1964 7 23 6.28 3.646 2.4479 28.2611 16.7944 +1964 7 24 2.2 3.634 2.3783 28.7833 16.6833 +1964 7 25 9.04 3.621 1.9802 27.2444 16.7222 +1964 7 26 0.06 3.608 1.9902 27.3167 16.8611 +1964 7 27 0.46 3.594 1.9205 28.1222 15.5833 +1964 7 28 2.57 3.58 1.4528 29.8611 16.1333 +1964 7 29 15.22 3.566 1.6817 29.8167 17.3389 +1964 7 30 1.99 3.551 2.0599 28.4389 17.0444 +1964 7 31 0.27 3.536 1.6021 27.7389 17.3111 +1964 8 1 0.47 3.521 1.413 27.6167 17.8 +1964 8 2 0.39 3.505 1.2538 29.9222 17.4 +1964 8 3 5.91 3.489 1.1245 30.9833 17.5667 +1964 8 4 5.75 3.472 1.1842 28.8333 17.1778 +1964 8 5 1.74 3.455 1.2041 27.3111 17.1667 +1964 8 6 0.02 3.438 1.1941 27.8722 16.6333 +1964 8 7 3.34 3.42 1.025 27.5 17.1111 +1964 8 8 4.62 3.402 1.0548 29.0167 17.2389 +1964 8 9 3.82 3.384 1.1145 28.4778 15.7778 +1964 8 10 15.38 3.365 1.6817 27.1722 17.1222 +1964 8 11 10.67 3.346 1.6121 25.0333 17.75 +1964 8 12 1.49 3.327 1.7215 27.8444 16.5556 +1964 8 13 0.37 3.307 1.3633 23.6333 8.6333 +1964 8 14 0.01 3.287 1.1742 21.6111 9.8 +1964 8 15 7.66 3.267 1.1245 17.3556 11.3833 +1964 8 16 57.33 3.246 2.1892 15.8 12.2611 +1964 8 17 0.67 3.225 4.0799 25.3222 13.4444 +1964 8 18 0.15 3.204 2.5276 26.3611 12.3778 +1964 8 19 1.6 3.182 1.8409 26.7167 13.3278 +1964 8 20 0.84 3.161 1.5623 26.9389 12.4389 +1964 8 21 0.26 3.139 1.5026 27.6389 15.1611 +1964 8 22 9.4 3.116 1.3832 27.8944 15.3722 +1964 8 23 0.03 3.094 1.6618 27.7333 17.5111 +1964 8 24 0.12 3.071 2.1693 28.6056 14.3611 +1964 8 25 0.03 3.048 1.4628 28.0222 14.0833 +1964 8 26 1.93 3.025 1.2737 28.2444 13.4778 +1964 8 27 15.06 3.001 1.2837 27.2889 14.2944 +1964 8 28 0.5 2.977 1.4628 26.7444 16.3556 +1964 8 29 31.57 2.954 1.5325 22.6722 16.8167 +1964 8 30 78.57 2.929 6.5975 21.65 17.0611 +1964 8 31 0.55 2.905 9.3141 27.6389 18.1389 +1964 9 1 0 2.88 7.1747 26.8944 13.8722 +1964 9 2 0 2.856 4.0202 26.3278 10.0278 +1964 9 3 0 2.831 2.428 26.9278 12.7278 +1964 9 4 0 2.806 2.0499 27.6278 13.6833 +1964 9 5 0.01 2.78 1.8111 28.4556 13.8389 +1964 9 6 0.05 2.755 1.6419 26.8222 12.6944 +1964 9 7 0.06 2.729 1.4926 26.2167 10.5889 +1964 9 8 0 2.704 1.3832 26.7444 8.5389 +1964 9 9 0.15 2.678 1.3235 26.8722 9.2333 +1964 9 10 0.32 2.652 1.2538 26.8389 15.2611 +1964 9 11 0.39 2.626 1.2439 27.1278 17.7611 +1964 9 12 4.05 2.599 1.2339 25.2056 15.5222 +1964 9 13 0.05 2.573 1.224 20.5444 11.8444 +1964 9 14 0 2.547 1.1842 21.3444 6.7222 +1964 9 15 0 2.52 1.1245 23.6167 5.5833 +1964 9 16 0 2.494 1.1046 24.4611 6.6 +1964 9 17 0.03 2.467 0.9931 23.3333 6.5556 +1964 9 18 2.64 2.44 0.9712 21.4167 10.6333 +1964 9 19 16.95 2.413 1.1245 21.8556 14.5444 +1964 9 20 8.13 2.386 1.5026 22.1278 14.5333 +1964 9 21 0.17 2.36 1.2041 23.1278 12.8667 +1964 9 22 0.17 2.333 1.0648 24.5389 12.9333 +1964 9 23 0.22 2.306 1.015 26.6778 14.0278 +1964 9 24 0.11 2.279 0.9822 23.2333 10.3444 +1964 9 25 0 2.252 0.9135 21.0278 5.1056 +1964 9 26 0 2.225 0.8906 21.0722 3.8222 +1964 9 27 0.48 2.198 0.8797 21.8278 9.8389 +1964 9 28 14.59 2.171 0.9016 22.7444 15.0944 +1964 9 29 133.98 2.144 4.9556 20.9667 16.1333 +1964 9 30 20.77 2.117 10.349 20.6556 16.25 +1964 10 1 15.54 2.09 11.9412 19.7222 14.1278 +1964 10 2 3.46 2.063 12.0407 23.3944 13.6222 +1964 10 3 8.05 2.036 8.2792 23.2444 15.0556 +1964 10 4 132.19 2.01 15.9216 19.6222 14.2667 +1964 10 5 20.69 1.983 31.8432 15.5 5.9222 +1964 10 6 0.01 1.956 29.0569 13.2444 0.1056 +1964 10 7 0 1.93 13.9314 15.0722 -1.0222 +1964 10 8 0.02 1.903 8.6176 16.0889 -1.1389 +1964 10 9 0 1.877 6.5677 18.3944 0.0778 +1964 10 10 0 1.851 5.1148 15.5056 0.2944 +1964 10 11 0 1.825 3.8212 16.3889 -2.4 +1964 10 12 0 1.799 3.3336 18.7889 -2.1778 +1964 10 13 0 1.773 3.0848 20.2278 0.5667 +1964 10 14 0.04 1.747 2.8858 17.8722 3.6278 +1964 10 15 10.3 1.722 2.7664 13.9056 6.5167 +1964 10 16 71.39 1.696 8.6176 12.1389 7.4889 +1964 10 17 0.1 1.671 8.2693 18.7722 8.4111 +1964 10 18 0.08 1.646 5.1347 24.3778 6.6889 +1964 10 19 0.16 1.621 3.7814 16.7611 4.7889 +1964 10 20 0 1.596 3.3734 10.6 -1.5667 +1964 10 21 0 1.572 3.0948 18.2944 -3.65 +1964 10 22 0 1.548 2.9057 21.9389 0.8722 +1964 10 23 0 1.523 2.7564 16.9833 0.2833 +1964 10 24 0 1.5 2.6271 15.4444 -2.9389 +1964 10 25 0 1.476 2.5475 18.45 -2.4444 +1964 10 26 0 1.452 2.4678 19.3056 -1.8278 +1964 10 27 0.07 1.429 2.3683 19.9667 -0.2111 +1964 10 28 2.79 1.406 2.3086 20.9778 2.6056 +1964 10 29 11.24 1.383 2.5077 19.8333 7.9667 +1964 10 30 0.01 1.361 2.4678 21.2278 4.9722 +1964 10 31 0 1.339 2.2688 18.4722 5.8222 +1964 11 1 0 1.317 2.1793 18.1389 5.2 +1964 11 2 0 1.295 2.1295 19.6778 0.4056 +1964 11 3 0 1.274 2.0698 20.5278 2.2833 +1964 11 4 0 1.252 2.0201 21.1167 1.3778 +1964 11 5 0 1.232 2.0002 20.4833 1.95 +1964 11 6 0 1.211 1.9703 21.5889 3.3222 +1964 11 7 0.04 1.191 1.9205 20.7111 0.8611 +1964 11 8 5.67 1.171 1.9504 17.0056 6.1222 +1964 11 9 0 1.151 1.9703 19.1167 4.0389 +1964 11 10 0 1.132 1.8708 21.5056 -0.0278 +1964 11 11 0 1.113 1.831 21.7833 0.5333 +1964 11 12 0 1.094 1.7912 20.5556 2 +1964 11 13 0.2 1.076 1.7812 22.5611 6.7333 +1964 11 14 0 1.058 1.7414 20.8722 1.6222 +1964 11 15 0.02 1.04 1.7016 20.8056 1.5056 +1964 11 16 0.44 1.023 1.7016 21.5611 5.0222 +1964 11 17 0.15 1.006 1.7016 20.9444 10.5111 +1964 11 18 0.23 0.99 1.6917 21.4833 10.9389 +1964 11 19 3.57 0.974 1.6917 19.6444 12.2111 +1964 11 20 3.43 0.958 1.6917 14.4056 1.8556 +1964 11 21 0 0.942 1.6718 7 -2.3278 +1964 11 22 0 0.927 1.5424 7.0056 -9.9611 +1964 11 23 0 0.913 1.4926 10.55 -8.2389 +1964 11 24 28.43 0.898 1.5325 8.4667 -1.8111 +1964 11 25 48.54 0.885 5.2641 13.6222 4.6611 +1964 11 26 0.02 0.871 6.3189 14.5278 1.5889 +1964 11 27 0 0.858 5.2442 17.3389 -1.0556 +1964 11 28 0.96 0.845 3.1843 14.1222 2.4111 +1964 11 29 0 0.833 2.647 12.6333 -0.8444 +1964 11 30 0.2 0.821 2.4081 5.0944 -6.6833 +1964 12 1 0 0.81 2.2091 3.5667 -11.6167 +1964 12 2 0.01 0.799 2.1096 9.9167 -8.8444 +1964 12 3 2.88 0.788 2.0499 15.0667 -0.5333 +1964 12 4 18.78 0.778 2.3484 17.1444 8.2611 +1964 12 5 1.07 0.769 2.9057 13.1444 4.5778 +1964 12 6 0.02 0.759 2.5077 6.1278 -3.0944 +1964 12 7 0 0.75 2.229 4.0667 -8.5722 +1964 12 8 0 0.742 2.1295 8.1222 -9.2222 +1964 12 9 0 0.734 2.0499 11.1556 -4.6556 +1964 12 10 0.02 0.727 1.9802 8.3333 -2.0278 +1964 12 11 8.11 0.72 1.9504 11.8556 1.7444 +1964 12 12 23.81 0.713 2.7863 15.4056 5.8222 +1964 12 13 0.07 0.707 3.6719 15.2111 2.6222 +1964 12 14 0.02 0.701 2.9156 9.0056 -3.1056 +1964 12 15 0 0.696 2.5375 5.4056 -5.8056 +1964 12 16 0.01 0.691 2.3385 6.8278 -7.4611 +1964 12 17 0.71 0.687 2.229 12.8944 -0.05 +1964 12 18 0.52 0.683 2.1693 8.2389 -5.5944 +1964 12 19 4.03 0.679 2.0201 1.9722 -12.5222 +1964 12 20 8.82 0.676 2.1494 6.7667 -4.3611 +1964 12 21 0.02 0.674 2.2987 4.0056 -1.6389 +1964 12 22 0.1 0.672 2.1295 7.6278 -1.4167 +1964 12 23 0.13 0.67 2.0599 12.9389 0.1722 +1964 12 24 13.37 0.669 2.0101 18.7278 4.5111 +1964 12 25 20.51 0.669 3.6421 16.6 7.4 +1964 12 26 26.82 0.668 4.3884 16.5444 9.6222 +1964 12 27 0.67 0.669 5.6323 14.2944 7.0111 +1964 12 28 0 0.669 5.0651 12.9556 -0.4556 +1964 12 29 0.01 0.671 3.8411 11.8722 -2.9611 +1964 12 30 0.26 0.672 3.1843 14.7278 -1.5833 +1964 12 31 0.08 0.674 2.9256 15.6111 3.1556 +1965 1 1 0.14 0.67 2.7166 13.4556 4.8389 +1965 1 2 3.19 0.68 2.5873 16.5889 1.8722 +1965 1 3 0 0.683 2.5176 9.5833 -1.7667 +1965 1 4 0 0.687 2.3783 10.75 -8.3 +1965 1 5 0 0.692 2.2887 11.3222 -4.7556 +1965 1 6 0 0.697 2.2489 12.8444 -0.9056 +1965 1 7 0 0.702 2.1793 10.4444 -2.9778 +1965 1 8 0.1 0.708 2.1196 18.3333 1.2833 +1965 1 9 0.88 0.714 2.0997 16.6944 6.4889 +1965 1 10 12.72 0.721 2.1494 15.4889 3.9611 +1965 1 11 1.27 0.728 2.4579 7.7389 -3.5944 +1965 1 12 0 0.735 2.2091 9.2944 -7.1056 +1965 1 13 0 0.744 2.0997 9.1278 -5.0889 +1965 1 14 0 0.752 2.04 6.0833 -4.7389 +1965 1 15 0.65 0.761 1.9703 2.9556 -6.5 +1965 1 16 14.24 0.77 1.9902 -0.8778 -6.3056 +1965 1 17 0.28 0.78 1.9902 -2.3778 -12.2167 +1965 1 18 0.02 0.79 1.9006 0.05 -12.0611 +1965 1 19 0 0.801 1.8509 3.8944 -13.0778 +1965 1 20 0 0.812 1.8509 10.1111 -9.4333 +1965 1 21 0 0.823 1.8807 13.1889 -5.4111 +1965 1 22 0.02 0.835 1.8807 16.0278 -3.8889 +1965 1 23 26.79 0.848 2.03 14.2278 2.1778 +1965 1 24 4.65 0.86 3.5028 14.6667 4.7278 +1965 1 25 0.2 0.873 3.1246 15.4611 -1.3333 +1965 1 26 0.14 0.887 2.6271 18.5333 0.2 +1965 1 27 0 0.901 2.3882 9.2056 -3.8611 +1965 1 28 0.01 0.915 2.2191 9.5278 -9.5611 +1965 1 29 0.72 0.93 2.1494 8.5222 -3.5 +1965 1 30 7.83 0.945 2.2091 3.8833 -4 +1965 1 31 0.05 0.961 2.1793 -1.6444 -13.1722 +1965 2 1 5.62 0.976 2.0101 4.4111 -10.5833 +1965 2 2 0.02 0.993 2.03 0.6167 -10.3611 +1965 2 3 0 1.009 1.9703 0.8833 -13.7556 +1965 2 4 0 1.026 1.9205 2.4111 -11.15 +1965 2 5 0.33 1.044 1.8708 7.2889 -12.6444 +1965 2 6 10.02 1.061 1.821 9.9056 -6.1444 +1965 2 7 31.01 1.079 3.0052 14.3944 3.3611 +1965 2 8 0.07 1.098 5.0452 18.6333 5.8389 +1965 2 9 4.67 1.116 4.0003 15.6333 5.9556 +1965 2 10 16.63 1.135 4.0401 17.9333 9.1722 +1965 2 11 6.92 1.155 4.866 20.2667 8.8611 +1965 2 12 11.2 1.174 4.5974 17.4 9.1056 +1965 2 13 0 1.194 4.1396 11.7056 -0.85 +1965 2 14 7.65 1.215 3.5326 4.9722 -2.0889 +1965 2 15 0.02 1.235 3.2838 5.9056 -8.9889 +1965 2 16 0.03 1.256 3.045 8.8056 -4.4889 +1965 2 17 0.25 1.277 2.846 8.2444 1.0278 +1965 2 18 0 1.299 2.7266 14.6056 -1.5444 +1965 2 19 0 1.321 2.5972 12.1722 -0.7222 +1965 2 20 0.02 1.343 2.4579 10.2778 -6.8889 +1965 2 21 1.16 1.365 2.3882 12.7944 -3.1 +1965 2 22 0.01 1.387 2.3484 7.2667 -9.9722 +1965 2 23 0.02 1.41 2.2489 8.9278 -8.4667 +1965 2 24 48.13 1.433 2.3783 6.1611 -2.05 +1965 2 25 4.52 1.457 6.1099 3.2222 -6.6556 +1965 2 26 0.11 1.48 6.0701 1.6556 -9.7833 +1965 2 27 0 1.504 4.5576 16.0333 -7.5444 +1965 2 28 0 1.528 3.4231 18.1722 -3.3778 +1965 3 1 0.89 1.552 3.1047 17.6944 -1.8667 +1965 3 2 21.5 1.576 3.1943 12.1444 3.8278 +1965 3 3 0.13 1.601 4.1695 12.1222 4.4556 +1965 3 4 5.74 1.626 3.7416 10.1167 3.1278 +1965 3 5 0.3 1.651 3.5824 3.9111 -5.5444 +1965 3 6 0.48 1.676 3.3137 1.8111 -5.2222 +1965 3 7 3.57 1.701 3.0848 4.8778 -3.5167 +1965 3 8 0.19 1.726 2.9554 4.9222 -2.6778 +1965 3 9 0 1.752 2.8062 10.8278 -4.2333 +1965 3 10 0 1.778 2.7067 8.6722 -3.4778 +1965 3 11 0 1.803 2.5674 9.2556 -6.2333 +1965 3 12 9.98 1.829 2.5574 5.6222 -2.35 +1965 3 13 0 1.856 2.5972 9.6222 -3.2111 +1965 3 14 0 1.882 2.5276 13.0889 -4.8389 +1965 3 15 0 1.908 2.4479 14.4222 -2.3778 +1965 3 16 0 1.935 2.3285 17.3222 -3.3611 +1965 3 17 22.76 1.961 2.4181 14.9556 2.4167 +1965 3 18 0.1 1.988 3.3137 19.1833 2.6056 +1965 3 19 1.4 2.014 2.8957 13.6278 -0.7278 +1965 3 20 5.71 2.041 2.7166 5.6667 -4.8111 +1965 3 21 0.05 2.068 2.5972 4.5667 -11.0778 +1965 3 22 0 2.095 2.4579 11.1 -9.7611 +1965 3 23 0.51 2.122 2.3882 18.3278 -1.9333 +1965 3 24 12.32 2.149 2.3783 15.5278 7.4833 +1965 3 25 31.11 2.176 3.3634 15.7667 9.5 +1965 3 26 46.31 2.203 11.3441 15.3 7.3889 +1965 3 27 0 2.23 8.4583 15.9667 1.3444 +1965 3 28 0.11 2.257 5.0054 17.7222 4.25 +1965 3 29 17.64 2.283 4.2192 15.2778 8.4389 +1965 3 30 1.39 2.31 4.4879 18.0778 7.45 +1965 3 31 1.21 2.337 3.7416 12.3111 3.0389 +1965 4 1 0.06 2.364 3.3833 10.2 1.5778 +1965 4 2 0.01 2.391 3.1346 17.4944 2.3889 +1965 4 3 3.52 2.418 2.9057 14.1111 -1.8556 +1965 4 4 0.68 2.445 2.846 16.9111 2.5944 +1965 4 5 0.06 2.472 2.7266 19.8444 5.8667 +1965 4 6 13.6 2.498 2.6768 22.9611 9.4111 +1965 4 7 4.26 2.525 3.0152 23.2556 10.8167 +1965 4 8 1 2.551 2.846 22.4278 7.1444 +1965 4 9 0.1 2.578 2.6569 25.3389 11.9111 +1965 4 10 0.03 2.604 2.4778 22.1167 6.0833 +1965 4 11 0.01 2.63 2.3982 23.3389 9.5 +1965 4 12 2.81 2.656 2.3484 25.2389 13.5167 +1965 4 13 0 2.682 2.2788 20.6944 8.5056 +1965 4 14 0.52 2.708 2.1494 19.5611 3.3833 +1965 4 15 13.51 2.734 2.1494 19.5222 7.8278 +1965 4 16 0.14 2.759 2.3882 16.0889 6.8556 +1965 4 17 0.03 2.785 2.239 21.0722 -0.0722 +1965 4 18 0.03 2.81 2.0997 24.9111 2.9111 +1965 4 19 4.22 2.835 2.0599 20.9333 6.4333 +1965 4 20 4.06 2.86 2.2091 18 8.3389 +1965 4 21 0.03 2.885 2.0698 21.5444 4.9944 +1965 4 22 0.03 2.909 1.9305 27.0167 6.0722 +1965 4 23 0.88 2.934 1.8708 28.1889 8.6722 +1965 4 24 4.63 2.958 1.8907 25.95 8.65 +1965 4 25 18.08 2.982 2.2489 21.2444 11.2111 +1965 4 26 31.15 3.005 2.8758 24.65 12.3222 +1965 4 27 13.48 3.029 4.6272 22.4444 11.4111 +1965 4 28 0.11 3.052 4.6471 14.9 5.9611 +1965 4 29 0.17 3.075 3.2639 14.7167 2.85 +1965 4 30 0 3.098 2.7763 21.45 2.7 +1965 5 1 0 3.12 2.5574 26.2833 4.8056 +1965 5 2 0 3.143 2.3683 27.0778 6.5222 +1965 5 3 0 3.165 2.2191 28.3444 5.5556 +1965 5 4 0 3.186 2.0997 27.9444 7.7222 +1965 5 5 0 3.208 2.0101 26.9444 8.8222 +1965 5 6 0.7 3.229 1.9404 27.3333 10.4944 +1965 5 7 4.79 3.25 1.8807 27.2833 10.4333 +1965 5 8 3.07 3.27 2.0897 26.7 10.8389 +1965 5 9 13.77 3.29 2.3285 25.8833 13.2778 +1965 5 10 4.55 3.31 2.2987 26.6833 12.0722 +1965 5 11 3.69 3.33 2.1992 25.6167 12.5611 +1965 5 12 0.8 3.349 2.1196 22.7444 11.5778 +1965 5 13 0 3.368 1.9205 24.1722 8.4556 +1965 5 14 0 3.387 1.7812 25.7556 6.7111 +1965 5 15 0 3.405 1.6519 25.95 8.6278 +1965 5 16 0.01 3.423 1.6021 26.55 10.4778 +1965 5 17 0.32 3.441 1.5524 23.9444 13.25 +1965 5 18 11.64 3.458 1.6419 24.4222 14.0444 +1965 5 19 0.05 3.475 1.8111 25.6278 12.8944 +1965 5 20 27.42 3.492 1.6817 25.3556 12.5333 +1965 5 21 3.48 3.508 2.9455 23.3278 13.8722 +1965 5 22 26.21 3.523 3.9008 24.0556 13.8944 +1965 5 23 5.27 3.539 4.0003 26.8389 12.3389 +1965 5 24 4.22 3.554 2.9057 28 12.8444 +1965 5 25 4.52 3.569 2.7465 27.3278 13.9722 +1965 5 26 2.92 3.583 2.7465 28.3111 14.5556 +1965 5 27 3.03 3.597 2.4678 25.0111 15.3778 +1965 5 28 2.55 3.61 2.2489 27.0278 12.4778 +1965 5 29 0.01 3.623 2.0698 23.8278 12.4722 +1965 5 30 0 3.636 1.8509 23.7389 6.6333 +1965 5 31 0 3.648 1.7514 25.1556 8.2278 +1965 6 1 0.01 3.66 1.6718 26.1833 9.8056 +1965 6 2 4.32 3.671 1.6021 27.8889 11.2722 +1965 6 3 2.5 3.682 1.5822 26.5278 14.6222 +1965 6 4 7.12 3.693 1.6718 21.9889 13.3444 +1965 6 5 0.03 3.703 1.5822 22.7611 13.5222 +1965 6 6 0.11 3.713 1.5126 25.9278 13.1444 +1965 6 7 6.07 3.722 1.413 22.8056 13.35 +1965 6 8 9.18 3.731 1.6618 24.35 14.9222 +1965 6 9 0.16 3.739 1.632 26.3944 14.8556 +1965 6 10 1.94 3.747 1.4926 27.7944 13.8889 +1965 6 11 27.65 3.755 1.6121 24.7556 16.0722 +1965 6 12 26.52 3.762 4.1496 25.0722 16.6444 +1965 6 13 0.28 3.768 3.7515 27.3111 15.3722 +1965 6 14 14 3.774 2.4778 25.75 15.4778 +1965 6 15 28.28 3.78 3.2341 19.2833 14.2111 +1965 6 16 1.98 3.785 4.4481 18.4667 12.0889 +1965 6 17 1.81 3.79 3.9406 20.7 11.1778 +1965 6 18 0 3.795 2.9554 21.3722 8.8667 +1965 6 19 0.01 3.798 2.4877 23.0333 6.4389 +1965 6 20 0 3.802 2.1892 26.0111 7.9667 +1965 6 21 0 3.805 2.0002 26.8778 10.5111 +1965 6 22 0.09 3.807 1.8509 27.65 12.0056 +1965 6 23 0.17 3.809 1.7414 27.1667 13.3556 +1965 6 24 1.64 3.811 1.7116 25.3444 14.0333 +1965 6 25 0.1 3.812 1.6618 25.0778 15.7389 +1965 6 26 0.05 3.813 1.5822 24.1611 12.55 +1965 6 27 0.46 3.813 1.4628 22.8722 14.3778 +1965 6 28 0.42 3.813 1.4528 27.3 15.6278 +1965 6 29 2.04 3.812 1.4429 28.9944 14.8722 +1965 6 30 4.02 3.811 1.5524 28.0667 15.2722 +1965 7 1 0 3.809 1.4727 27.2167 14.8667 +1965 7 2 0.02 3.807 1.3633 26.75 15.3778 +1965 7 3 3.44 3.804 1.3434 25.9056 16.1389 +1965 7 4 3.67 3.801 1.3334 28.6167 14.8056 +1965 7 5 8.19 3.798 1.3633 28.3611 15.7944 +1965 7 6 0.38 3.794 1.4031 28.8278 14.9222 +1965 7 7 8.49 3.789 1.3434 27.55 15.2556 +1965 7 8 6.63 3.785 1.423 28.5889 16.55 +1965 7 9 8.39 3.779 1.5723 29.2944 16.0556 +1965 7 10 6.27 3.773 1.7116 28.1889 16.8833 +1965 7 11 8.11 3.767 1.5325 27.95 17.3389 +1965 7 12 2.53 3.76 1.7315 25.4278 16.1778 +1965 7 13 3.63 3.753 1.7116 26.7444 16.7611 +1965 7 14 9.01 3.746 1.4827 28.2389 16.05 +1965 7 15 4.09 3.738 1.3434 27.1111 16.8056 +1965 7 16 1.22 3.729 1.5424 28.2333 15.85 +1965 7 17 0.01 3.72 1.3533 29.1333 14.2667 +1965 7 18 10.55 3.711 1.2638 29.2278 14.3889 +1965 7 19 5.14 3.701 1.3931 27.0833 15.2167 +1965 7 20 0.03 3.691 1.4827 25.8778 15.1167 +1965 7 21 0.01 3.68 1.3732 26.95 15.1222 +1965 7 22 0.9 3.669 1.224 28.4333 14.2778 +1965 7 23 0.45 3.658 1.1344 29.2167 16.3722 +1965 7 24 3.09 3.646 1.0946 30.9611 16.8222 +1965 7 25 6.1 3.634 1.0747 30.1667 18.3167 +1965 7 26 5.54 3.621 1.3633 28.8556 18.2222 +1965 7 27 14.83 3.608 2.0002 27.3222 17.9111 +1965 7 28 1.32 3.594 2.5077 26.3722 17.7833 +1965 7 29 7.07 3.58 1.5026 26.0167 14.5556 +1965 7 30 6.92 3.566 1.7713 26.2444 14.4667 +1965 7 31 2.41 3.551 1.6618 26.5722 15.1333 +1965 8 1 0.13 3.536 1.4827 26.1111 15.3333 +1965 8 2 0.06 3.521 1.2538 26.1389 13.4611 +1965 8 3 0.23 3.505 1.1344 26.5556 10.8167 +1965 8 4 0.35 3.489 1.0747 28.0667 11.55 +1965 8 5 0.04 3.472 1.0648 28.7333 12.7611 +1965 8 6 0.06 3.455 1.0349 28.7 13.1167 +1965 8 7 11.11 3.438 1.025 27.5667 14.6556 +1965 8 8 6.23 3.42 1.0648 26.1278 16.2056 +1965 8 9 7.13 3.402 1.4031 27.3056 16.1111 +1965 8 10 0.18 3.384 1.2837 27.3333 14.0222 +1965 8 11 0.51 3.365 1.0648 26.4222 12.7944 +1965 8 12 2.38 3.346 1.0051 28.2167 14.2056 +1965 8 13 1.05 3.327 1.0349 28.7611 16.0667 +1965 8 14 0.37 3.307 1.025 30.1111 16.4222 +1965 8 15 0.18 3.287 1.015 30.55 17.8 +1965 8 16 1.01 3.267 0.9354 31.8889 16.9333 +1965 8 17 3.02 3.246 0.9652 31.8111 16.2667 +1965 8 18 5.99 3.225 0.9314 31.2111 16.1667 +1965 8 19 11 3.204 1.1742 30.8111 15.9278 +1965 8 20 5.66 3.182 1.632 28.2111 15.9889 +1965 8 21 20.53 3.161 1.3732 27.5778 18.2 +1965 8 22 11.32 3.139 2.0599 28 17.8333 +1965 8 23 8.26 3.116 2.3086 28.0667 17.25 +1965 8 24 9.7 3.094 1.7812 26.6 17.4556 +1965 8 25 4.55 3.071 1.6718 27.0444 17.5278 +1965 8 26 0.22 3.048 1.413 29.7722 15.3722 +1965 8 27 12.65 3.025 1.413 30.5667 14.7 +1965 8 28 0.25 3.001 1.9305 28.1278 16.1222 +1965 8 29 0.07 2.977 1.224 24.9389 11.1556 +1965 8 30 0 2.954 1.0449 24.4111 8.1778 +1965 8 31 0 2.929 0.9822 25.3611 9.4889 +1965 9 1 0.66 2.905 0.9364 26.1778 12.2056 +1965 9 2 0.23 2.88 0.9254 21.9056 13.6 +1965 9 3 0.02 2.856 0.9026 21.8056 13.5111 +1965 9 4 0.01 2.831 0.8906 23.3556 12.4278 +1965 9 5 0.02 2.806 0.8359 24.3222 14.2944 +1965 9 6 0 2.78 0.7812 25.6611 15.0889 +1965 9 7 0 2.755 0.7921 26.0167 10.3611 +1965 9 8 0 2.729 0.7712 27.35 8.4222 +1965 9 9 0.08 2.704 0.7513 27.6056 8.7833 +1965 9 10 8.86 2.678 0.803 28.3611 15.3444 +1965 9 11 0.06 2.652 0.8687 28.4889 16.2611 +1965 9 12 11.08 2.626 0.9364 24.6056 18.1722 +1965 9 13 0.02 2.599 1.0449 25.6278 16.4944 +1965 9 14 0.09 2.573 1.015 27.6222 14.5111 +1965 9 15 1.84 2.547 0.9026 28.4056 15.5556 +1965 9 16 3.22 2.52 0.8687 27.8667 15.4556 +1965 9 17 1.05 2.494 0.814 27.8333 15.8611 +1965 9 18 0.08 2.467 0.7921 27.2278 15.3667 +1965 9 19 0.46 2.44 0.7921 28.8278 14.5944 +1965 9 20 0.24 2.413 0.7314 28.5222 14.1333 +1965 9 21 0.16 2.386 0.7314 28.6167 12.6278 +1965 9 22 10.01 2.36 0.7115 26.6722 13.8944 +1965 9 23 17.21 2.333 1.3434 25.1611 16.9333 +1965 9 24 41.06 2.306 2.6967 22.0944 14.35 +1965 9 25 0.26 2.279 3.1843 20.4556 7.3444 +1965 9 26 0.03 2.252 1.8608 20.8444 5.5444 +1965 9 27 0 2.225 1.3235 20.2278 9.2611 +1965 9 28 0 2.198 1.1842 19.5944 9.0167 +1965 9 29 0 2.171 1.1344 21.8833 10.3889 +1965 9 30 35.2 2.144 1.1245 19.7111 12.5167 +1965 10 1 55.57 2.117 5.0551 25.4611 15.3222 +1965 10 2 0.07 2.09 6.5378 23.9278 11.4944 +1965 10 3 0 2.063 5.483 22.5333 7.1333 +1965 10 4 0 2.036 4.5974 19.7667 5.3333 +1965 10 5 0.1 2.01 2.3982 16.3056 3.1556 +1965 10 6 3.41 1.983 1.9504 18.2611 2.1833 +1965 10 7 22.35 1.956 2.2788 19.2333 7.5556 +1965 10 8 0.09 1.93 2.846 20.3667 6.1111 +1965 10 9 0 1.903 2.1196 19.5278 2.7722 +1965 10 10 0 1.877 1.8011 19.1222 2.1667 +1965 10 11 0 1.851 1.622 20.5389 2.1 +1965 10 12 0 1.825 1.5325 20.8056 5.5111 +1965 10 13 0 1.799 1.4628 21.2889 3.0222 +1965 10 14 0.01 1.773 1.3931 22.9056 4.25 +1965 10 15 0.37 1.747 1.3533 24.4889 6.9556 +1965 10 16 2.03 1.722 1.3135 25.1111 7.2611 +1965 10 17 0.02 1.696 1.224 22.9722 8.5389 +1965 10 18 0.08 1.671 1.1245 18.5611 5.5444 +1965 10 19 1.17 1.646 1.1245 17.0222 9.8389 +1965 10 20 5.52 1.621 1.1941 18.0333 12.6167 +1965 10 21 11.2 1.596 1.4727 16.8667 12.7778 +1965 10 22 4.04 1.572 1.8708 19.2611 9.4222 +1965 10 23 0.4 1.548 1.6121 16.7 4.5556 +1965 10 24 0.01 1.523 1.423 11.0778 2.0167 +1965 10 25 0 1.5 1.2638 13.7667 -3.9889 +1965 10 26 0 1.476 1.2339 17.85 -3.1389 +1965 10 27 0 1.452 1.2538 18.6333 -1.2611 +1965 10 28 0 1.429 1.2439 17.4111 -0.4333 +1965 10 29 0 1.406 1.1742 14.6111 -3.6222 +1965 10 30 0 1.383 1.1046 17.3 -5.4222 +1965 10 31 0 1.361 1.1046 20.5611 -2.3944 +1965 11 1 0 1.339 1.0847 17.8556 1.7 +1965 11 2 0 1.317 1.0648 18.2667 -3.8611 +1965 11 3 0.02 1.295 1.0548 20.8889 -2.7222 +1965 11 4 0.02 1.274 1.0449 19.9167 2.4222 +1965 11 5 0 1.252 1.0349 17.4056 4.3 +1965 11 6 0 1.232 1.0349 19.2611 4.1111 +1965 11 7 0 1.211 1.025 20.8389 1.5611 +1965 11 8 0 1.191 1.0051 20.8167 2.0722 +1965 11 9 0 1.171 1.015 20.3889 4.3167 +1965 11 10 18.06 1.151 1.0548 15.0667 7.1444 +1965 11 11 0.46 1.132 1.3434 15.2667 6.6167 +1965 11 12 2.4 1.113 1.2936 11.8722 6.8389 +1965 11 13 0.53 1.094 1.1444 17.5167 6.4278 +1965 11 14 0.1 1.076 1.1245 18 2.25 +1965 11 15 0 1.058 1.0747 16.7 -0.7833 +1965 11 16 0.01 1.04 1.0349 19.2556 3.6556 +1965 11 17 0.33 1.023 1.0349 14.0056 0.9167 +1965 11 18 0 1.006 0.9951 9.7333 -4.0167 +1965 11 19 0 0.99 0.9812 15.0444 -1.2833 +1965 11 20 0.03 0.974 0.9752 15.4111 -3.9833 +1965 11 21 21.64 0.958 1.0051 12.2333 -2.0833 +1965 11 22 1.32 0.942 1.3931 13.9556 3.8778 +1965 11 23 0.06 0.927 1.4429 15.05 -1.9 +1965 11 24 0.35 0.913 1.1941 15.05 -1.0556 +1965 11 25 4.01 0.898 1.1444 9.9056 2.8167 +1965 11 26 0.03 0.885 1.1245 16.5889 2.2611 +1965 11 27 6.09 0.871 1.1842 16.4778 5.1278 +1965 11 28 0 0.858 1.214 12.8722 0.4 +1965 11 29 0 0.845 1.0946 8.0222 -3.7167 +1965 11 30 0 0.833 1.0449 4.0167 -7.6556 +1965 12 1 0 0.821 1.015 7.1222 -10.1167 +1965 12 2 0 0.81 0.9941 13.3278 -8.5778 +1965 12 3 0.04 0.799 1.025 12.2 -2.5833 +1965 12 4 0 0.788 1.0548 9.8222 -2.25 +1965 12 5 0 0.778 1.025 16.5556 -5.8444 +1965 12 6 0 0.769 0.9583 12.3222 -2.3944 +1965 12 7 0 0.759 0.9364 7.9333 -4.5889 +1965 12 8 0 0.75 0.9155 13.0222 -8.9667 +1965 12 9 0 0.742 0.9165 15.7889 -5.4889 +1965 12 10 0 0.734 0.9085 15.5222 -5.2333 +1965 12 11 0.01 0.727 0.8966 16.8056 -1.2444 +1965 12 12 1.72 0.72 0.9065 15.6889 2.7722 +1965 12 13 0.21 0.713 0.9065 18.1167 5.8556 +1965 12 14 0.02 0.707 0.9274 12.9444 2.5056 +1965 12 15 0.05 0.701 0.8906 10.9111 4.1389 +1965 12 16 1.43 0.696 0.8936 9.8722 5.0333 +1965 12 17 0.03 0.691 0.9016 10.5778 1.8056 +1965 12 18 0 0.687 0.8827 7.7444 -3.0333 +1965 12 19 0.02 0.683 0.8498 6.3056 -2.1833 +1965 12 20 0.2 0.679 0.7891 4.6444 -9.15 +1965 12 21 0.05 0.676 0.82 6.0944 -4.4222 +1965 12 22 0 0.674 0.8438 11.5 -6.3056 +1965 12 23 0 0.672 0.8329 15.3778 -5.7667 +1965 12 24 0 0.67 0.8279 13.5556 0.2389 +1965 12 25 6.97 0.669 0.8528 12.75 1.95 +1965 12 26 0 0.669 0.9364 7.5333 -4.4778 +1965 12 27 0 0.668 0.8866 7.7556 -9.3833 +1965 12 28 0 0.669 0.8319 9.6333 -8.2611 +1965 12 29 0 0.669 0.82 12.5 -7.8111 +1965 12 30 0 0.671 0.8299 17.1167 -5.1833 +1965 12 31 0 0.672 0.8289 17.4 -0.7944 +1966 1 1 1.06 0.67 0.8329 16.7833 3.9667 +1966 1 2 7.86 0.68 0.8349 16.2389 9.4111 +1966 1 3 1.43 0.683 0.8866 13.1111 5.2556 +1966 1 4 0.07 0.687 0.9235 9.5833 -3.1333 +1966 1 5 27.89 0.692 1.0051 8.4111 0.3222 +1966 1 6 0.53 0.697 1.7116 12.1111 3.8833 +1966 1 7 0 0.702 1.632 13.6278 -1.6111 +1966 1 8 0.01 0.708 1.2439 6.9111 -5.9444 +1966 1 9 0 0.714 1.0946 8.35 -10.5389 +1966 1 10 0.04 0.721 1.0349 10.9389 -7.5278 +1966 1 11 0 0.728 1.0051 8.9611 -4.9833 +1966 1 12 0.01 0.735 0.9702 7.4444 -7.65 +1966 1 13 0.76 0.744 0.9483 5.4444 -3.2 +1966 1 14 0.07 0.752 0.9493 7.3 0.1667 +1966 1 15 28.33 0.761 0.9891 3.3889 -1.9389 +1966 1 16 1 0.77 1.1145 4.7222 -2.5611 +1966 1 17 0 0.78 1.0747 2.4111 -8.5 +1966 1 18 0 0.79 1.0349 2.1222 -8.4444 +1966 1 19 0.05 0.801 1.015 0.1111 -9.7667 +1966 1 20 0.54 0.812 0.8986 2.6889 -13.5667 +1966 1 21 0.02 0.823 0.8916 4.1722 -12.9111 +1966 1 22 18.17 0.835 0.9881 2.0889 -5.3889 +1966 1 23 1.09 0.848 1.0946 1.15 -5.3722 +1966 1 24 0 0.86 0.9782 1.5444 -11.2389 +1966 1 25 3.22 0.873 0.9762 0.75 -6.9389 +1966 1 26 8.56 0.887 0.9533 -0.1944 -6.2611 +1966 1 27 0.31 0.901 0.8956 1.8833 -9.7722 +1966 1 28 0 0.915 0.8458 5.7167 -7.3667 +1966 1 29 9.73 0.93 0.8458 1.0167 -9.55 +1966 1 30 0.01 0.945 0.6468 -6.65 -14.5667 +1966 1 31 0.06 0.961 0.6966 -0.6222 -15.3722 +1966 2 1 7.38 0.976 0.7463 5.3278 -7.7389 +1966 2 2 0.15 0.993 0.7961 2.2667 -4.3222 +1966 2 3 0 1.009 0.7961 1.6833 -8.8556 +1966 2 4 0.31 1.026 0.7961 -0.4611 -8.6389 +1966 2 5 0.01 1.044 0.7961 1.3667 -12.65 +1966 2 6 0.25 1.061 0.8458 8.35 -12.7167 +1966 2 7 0.13 1.079 0.9155 8.2944 -8.2833 +1966 2 8 0.09 1.098 1.0051 15.0278 -0.8833 +1966 2 9 0.51 1.116 1.4628 10.35 0.2389 +1966 2 10 10.63 1.135 1.7713 13.5278 3.5944 +1966 2 11 0.56 1.155 3.3037 13.6667 8.0556 +1966 2 12 48.21 1.174 3.254 12.8944 7.1778 +1966 2 13 71 1.194 13.4338 15.2056 6.7722 +1966 2 14 0.09 1.215 18.4093 14.6333 0.3056 +1966 2 15 23.18 1.235 13.7324 11.0611 4.95 +1966 2 16 16.87 1.256 9.3141 11.1389 6.0722 +1966 2 17 0.01 1.277 7.5628 8.6556 -2.1722 +1966 2 18 0.04 1.299 6.0104 5.9111 -3.9167 +1966 2 19 0 1.321 4.5974 11.9833 -4.9389 +1966 2 20 0 1.343 3.4828 9.7444 -3.8389 +1966 2 21 0 1.365 3.0152 8.7556 -5.9444 +1966 2 22 0.01 1.387 2.7365 8.4944 -5.9556 +1966 2 23 6.26 1.41 2.5276 5.1944 -4.8667 +1966 2 24 9.65 1.433 2.5176 2.8444 -3.2167 +1966 2 25 0.02 1.457 2.5475 8.5333 -1.1056 +1966 2 26 0.01 1.48 2.5176 9.1444 -2.6222 +1966 2 27 5.47 1.504 2.3086 5.2611 -3.1944 +1966 2 28 18.79 1.528 2.8758 9.0778 -0.2944 +1966 3 1 0.08 1.552 4.0003 13.0333 1.3389 +1966 3 2 0.03 1.576 3.1843 14.65 -2.9833 +1966 3 3 19.93 1.601 2.7664 13.2944 3.2111 +1966 3 4 40.77 1.626 7.2045 17.7222 7.7444 +1966 3 5 0.26 1.651 7.5628 11.3667 -1.5389 +1966 3 6 0.07 1.676 6.2293 1.3222 -6.5333 +1966 3 7 0.04 1.701 4.4481 1.6278 -6.8333 +1966 3 8 0 1.726 3.3634 6.4333 -8.8778 +1966 3 9 0 1.752 3.0152 10.6889 -8.6611 +1966 3 10 0 1.778 2.8161 14.7278 -5.9167 +1966 3 11 0 1.803 2.6271 18.5778 -4.0722 +1966 3 12 1.08 1.829 2.4877 20.6167 -2.2944 +1966 3 13 0.13 1.856 2.3584 19.65 2.4611 +1966 3 14 0.61 1.882 2.2589 19.7833 4.8556 +1966 3 15 4.7 1.908 2.1892 16.3556 7.9889 +1966 3 16 1.27 1.935 2.1992 13.5722 4.9111 +1966 3 17 0.03 1.961 2.0897 15.9167 2.0944 +1966 3 18 0.12 1.988 1.9703 19.2611 -0.6889 +1966 3 19 2.36 2.014 1.9404 17.6222 3.9833 +1966 3 20 0.1 2.041 1.8807 18.5833 1.7 +1966 3 21 0.01 2.068 1.8011 20.6444 -0.9611 +1966 3 22 0.17 2.095 1.7613 24.4333 5.3222 +1966 3 23 0.84 2.122 1.7116 23.0111 6.1667 +1966 3 24 3.2 2.149 1.7016 15.6389 2.85 +1966 3 25 0 2.176 1.6618 10.1 -4.2778 +1966 3 26 1.36 2.203 1.5922 11.2833 -3.85 +1966 3 27 0.01 2.23 1.5922 9.65 -2.5667 +1966 3 28 0 2.257 1.5026 8.2444 -4.35 +1966 3 29 0.02 2.283 1.4329 12.9222 -6.9944 +1966 3 30 0.13 2.31 1.4628 16.65 -2.7333 +1966 3 31 1.57 2.337 1.4827 14.75 0.55 +1966 4 1 0.09 2.364 1.4429 19.6889 0.3222 +1966 4 2 0.14 2.391 1.4031 14.1278 2.5778 +1966 4 3 6.88 2.418 1.3135 20.7333 -2.3722 +1966 4 4 2.81 2.445 1.413 16.45 3.5333 +1966 4 5 0.01 2.472 1.3931 11.8833 -2.2167 +1966 4 6 0 2.498 1.2936 11.7444 -2.1278 +1966 4 7 0.04 2.525 1.2936 16.35 -2.7944 +1966 4 8 1.57 2.551 1.3036 14.1056 0.3444 +1966 4 9 0 2.578 1.2737 11.5056 0.1389 +1966 4 10 0 2.604 1.1941 12.0611 -3.0111 +1966 4 11 0.02 2.63 1.1742 16.5333 -3.5167 +1966 4 12 0.21 2.656 1.1742 21.4278 4.2111 +1966 4 13 9.92 2.682 1.214 22.3111 8.1833 +1966 4 14 4.74 2.708 1.2339 16.8444 4.6333 +1966 4 15 2.66 2.734 1.2837 13.2056 3.7611 +1966 4 16 0.01 2.759 1.3235 15.5556 0.9444 +1966 4 17 0 2.785 1.2439 19.1389 -0.5889 +1966 4 18 0.01 2.81 1.224 22.6167 2.65 +1966 4 19 0.74 2.835 1.2339 18.8278 9.75 +1966 4 20 2.76 2.86 1.2538 17.9944 9.7944 +1966 4 21 1.08 2.885 1.2538 19.4889 12.8556 +1966 4 22 26.27 2.909 1.6519 19.3611 13.0722 +1966 4 23 0.05 2.934 2.2887 22.8444 9.9722 +1966 4 24 0.02 2.958 1.8807 25.2333 8.1944 +1966 4 25 1.63 2.982 1.6519 23.5611 12.1111 +1966 4 26 8.52 3.005 1.6121 19.7444 11.95 +1966 4 27 12.28 3.029 1.7116 18.7667 12.8333 +1966 4 28 27.46 3.052 2.0599 22.55 11.9278 +1966 4 29 12.42 3.075 3.1047 19.8056 12.7167 +1966 4 30 32.89 3.098 6.5478 19.7278 13.8944 +1966 5 1 7.79 3.12 6.3288 23.7667 12.3444 +1966 5 2 6.73 3.143 5.8512 17.8222 11.4778 +1966 5 3 0 3.165 4.5675 20.4722 5.8944 +1966 5 4 0 3.186 3.3634 21.6667 5.6 +1966 5 5 0 3.208 2.836 22.8889 3.4667 +1966 5 6 0.69 3.229 2.5475 25.0278 7.4889 +1966 5 7 1.24 3.25 2.3186 25.0889 9.8833 +1966 5 8 2.83 3.27 2.239 26.3389 8.7222 +1966 5 9 0.8 3.29 2.1594 26.3 7.5944 +1966 5 10 0 3.31 2.0101 18.2667 0.1222 +1966 5 11 0.01 3.33 1.8907 17.9222 0.1389 +1966 5 12 1.06 3.349 1.821 17.15 8.9667 +1966 5 13 2.86 3.368 1.831 18.9444 10.4778 +1966 5 14 10.87 3.387 1.8708 22.7111 11.85 +1966 5 15 0.06 3.405 2.0897 23.7278 8.2056 +1966 5 16 2.23 3.423 1.7116 20.3556 7.8333 +1966 5 17 0.39 3.441 1.6419 22.8944 12.2722 +1966 5 18 1.86 3.458 1.6121 22.0278 13.1611 +1966 5 19 6.23 3.475 1.6121 24.7111 12.2111 +1966 5 20 1.52 3.492 1.7215 26.2056 11.9778 +1966 5 21 3.14 3.508 1.7613 26.2611 10.4889 +1966 5 22 6.29 3.523 1.6718 25.9667 12.8722 +1966 5 23 0.06 3.539 1.7215 23.8333 14.05 +1966 5 24 5.4 3.554 1.6519 18.5 11.3667 +1966 5 25 4.78 3.569 1.7414 22.6222 13.1111 +1966 5 26 19.55 3.583 2.03 20.3056 14.4722 +1966 5 27 20.23 3.597 2.7564 20.6333 15.3 +1966 5 28 0.78 3.61 3.4132 25.85 14.1444 +1966 5 29 3.38 3.623 2.7664 27.2611 11.2889 +1966 5 30 0 3.636 2.5176 23.6778 9.5389 +1966 5 31 0 3.648 2.0798 19.8333 8.2278 +1966 6 1 0 3.66 1.8608 18.9722 2.9944 +1966 6 2 0 3.671 1.7116 22.9333 2.0556 +1966 6 3 0.01 3.682 1.632 24.9778 5.0889 +1966 6 4 0 3.693 1.5623 25.6667 8.6 +1966 6 5 0 3.703 1.5126 25.8333 10.3167 +1966 6 6 0.03 3.713 1.4528 26.25 9.7889 +1966 6 7 5.92 3.722 1.4329 26.9333 13.9 +1966 6 8 11.77 3.731 1.5623 27.8833 13.7 +1966 6 9 10.78 3.739 2.0997 26.1333 14.6167 +1966 6 10 9.34 3.747 2.3285 26.6389 16.2056 +1966 6 11 0.24 3.755 2.239 26.4 14.4944 +1966 6 12 0 3.762 1.7315 27 10.0167 +1966 6 13 0 3.768 1.5623 28.2889 11.3833 +1966 6 14 0.81 3.774 1.4628 24.1278 13.1056 +1966 6 15 0.03 3.78 1.4429 27.1667 13.2056 +1966 6 16 10.62 3.785 1.3931 28.25 13.3278 +1966 6 17 0.9 3.79 1.5524 25.1278 14.05 +1966 6 18 4.45 3.795 1.4827 21.9333 13.55 +1966 6 19 0.06 3.798 1.4628 24.1 10.6278 +1966 6 20 0.04 3.802 1.3235 25.8056 9.9 +1966 6 21 0 3.805 1.2737 27.2833 10.4056 +1966 6 22 0 3.807 1.2538 28.2167 10.7833 +1966 6 23 0 3.809 1.214 29.1111 11.6556 +1966 6 24 0.06 3.811 1.1543 30.0667 12.9056 +1966 6 25 0.13 3.812 1.1046 30.4389 14.5667 +1966 6 26 1.11 3.813 1.0847 30.3389 15.8611 +1966 6 27 0.8 3.813 1.1046 30.2778 15.0167 +1966 6 28 3.38 3.813 1.1941 29.8556 15.7056 +1966 6 29 3.98 3.812 1.1444 30.2333 15.6722 +1966 6 30 5.51 3.811 1.2538 29.1778 15.2 +1966 7 1 10.58 3.809 1.224 24.6833 16.6667 +1966 7 2 7.4 3.807 1.5623 23.0722 16.9611 +1966 7 3 8.11 3.804 1.4926 27.6444 17 +1966 7 4 0.36 3.801 1.9305 27.8667 16.1167 +1966 7 5 10.08 3.798 1.5822 27.2611 16.0833 +1966 7 6 2.88 3.794 1.3931 28.9778 16.9722 +1966 7 7 4.48 3.789 1.3135 30.1611 15.2222 +1966 7 8 0 3.785 1.2339 29.2889 15.2167 +1966 7 9 0 3.779 1.1245 30.2889 12.7389 +1966 7 10 0.31 3.773 1.0349 30.6722 14.2056 +1966 7 11 0.1 3.767 0.9603 31.7278 15.5833 +1966 7 12 0.15 3.76 0.9274 31.8778 17.1556 +1966 7 13 10.07 3.753 0.9384 29.3 17.8833 +1966 7 14 1.61 3.746 1.0349 32.3611 18.3389 +1966 7 15 9.82 3.738 1.1046 30.0167 17.8778 +1966 7 16 0.02 3.729 1.1842 23.5333 17.3333 +1966 7 17 2.92 3.72 1.0548 23.0167 17.2111 +1966 7 18 0 3.711 0.9822 28.5556 16.1333 +1966 7 19 5.41 3.701 0.9254 29.1889 16.7444 +1966 7 20 0.01 3.691 0.9822 29.05 16.9333 +1966 7 21 0 3.68 0.8468 27.1833 15.6222 +1966 7 22 0.01 3.669 0.7812 27.5 11.8 +1966 7 23 0 3.658 0.7513 27.9167 11 +1966 7 24 0 3.646 0.7115 27.8556 11.7278 +1966 7 25 0.03 3.634 0.6528 29.1389 13.2889 +1966 7 26 0.03 3.621 0.6727 30.7222 14.9444 +1966 7 27 0.01 3.608 0.7115 32.0722 14.1667 +1966 7 28 2.87 3.594 0.6926 32.7778 14.6889 +1966 7 29 3.72 3.58 0.7095 29.4278 17.0389 +1966 7 30 22.37 3.566 0.8876 24.1722 16.4667 +1966 7 31 0.16 3.551 1.1643 26.3722 12.7333 +1966 8 1 0 3.536 0.8628 27.6556 12.9889 +1966 8 2 0.09 3.521 0.7463 27.9444 13.7111 +1966 8 3 31.8 3.505 0.7553 26.9889 16.6056 +1966 8 4 1.47 3.489 1.9205 25.6167 15.6389 +1966 8 5 0.86 3.472 1.2837 27.1278 15.6611 +1966 8 6 1.06 3.455 0.8986 26.2056 15.5056 +1966 8 7 11.03 3.438 0.9105 26.2 16.6944 +1966 8 8 5.77 3.42 0.8518 26.3222 15.7889 +1966 8 9 11.86 3.402 1.1344 26.3 16.0611 +1966 8 10 10.33 3.384 1.1046 27.2444 14.9056 +1966 8 11 9.75 3.365 1.025 25.7444 17.4722 +1966 8 12 10.25 3.346 1.3434 25.5167 16.5167 +1966 8 13 11.22 3.327 1.9305 26.1833 17.1944 +1966 8 14 11.03 3.307 2.4081 28.4556 17.4722 +1966 8 15 6.29 3.287 1.7116 29.2111 17.2333 +1966 8 16 3.85 3.267 1.5623 28.8944 17.4389 +1966 8 17 6.61 3.246 1.2837 29.2667 18.2611 +1966 8 18 3.71 3.225 1.2339 29.4611 17.3444 +1966 8 19 3.49 3.204 1.2936 28.7611 16.6278 +1966 8 20 12.27 3.182 1.224 28.6778 17.2111 +1966 8 21 3.02 3.161 1.821 28.4556 17 +1966 8 22 5.39 3.139 1.4528 28.6833 16.6389 +1966 8 23 0.17 3.116 1.4031 26.9278 17.0056 +1966 8 24 0.05 3.094 1.0747 25.6222 13.1556 +1966 8 25 6.42 3.071 0.9324 23.8556 14.15 +1966 8 26 19.99 3.048 1.5524 22.9444 13.5056 +1966 8 27 0 3.025 1.4827 25.7944 10.4222 +1966 8 28 0 3.001 1.1742 26.8667 11.3111 +1966 8 29 0 2.977 0.9593 26.8611 13.0667 +1966 8 30 0.01 2.954 0.8906 25.4056 13.8444 +1966 8 31 5.75 2.929 0.9135 27.0556 13.3389 +1966 9 1 0.32 2.905 0.9364 28.1944 13.8222 +1966 9 2 0.87 2.88 0.8797 28.6556 13.5611 +1966 9 3 0.48 2.856 1.0449 28.85 12.9222 +1966 9 4 6.09 2.831 0.9364 27.7833 14.8111 +1966 9 5 0.21 2.806 0.803 26.7889 16.65 +1966 9 6 0.04 2.78 0.7712 26.3556 10.7444 +1966 9 7 0 2.755 0.7613 24.8667 12.2667 +1966 9 8 0 2.729 0.7314 24.9278 10.3778 +1966 9 9 0 2.704 0.7115 25.2611 9.5278 +1966 9 10 0 2.678 0.7015 26.2278 9.6 +1966 9 11 0.09 2.652 0.6627 25.6389 10.5167 +1966 9 12 6.2 2.626 0.606 22.1889 11.1667 +1966 9 13 75.06 2.599 1.2439 17.4444 13.45 +1966 9 14 1.16 2.573 4.9456 22.0556 14.1444 +1966 9 15 1.6 2.547 3.2739 22.8222 11.7444 +1966 9 16 0.05 2.52 1.7912 20.7222 10.9389 +1966 9 17 0.28 2.494 1.4329 18.9444 10.9111 +1966 9 18 7.03 2.467 1.3334 16.7833 11.3444 +1966 9 19 28.8 2.44 1.6817 17.1056 12.5389 +1966 9 20 0.74 2.413 2.647 22.0556 12.7278 +1966 9 21 11.28 2.386 2.1594 21.1889 13.2056 +1966 9 22 0.02 2.36 2.1395 20.7056 9.8833 +1966 9 23 0 2.333 1.7315 22.4833 8.8167 +1966 9 24 0 2.306 1.4429 22.5389 6.5111 +1966 9 25 0.12 2.279 1.2837 24.1167 5.2778 +1966 9 26 3.66 2.252 1.2041 21.6278 8.4833 +1966 9 27 0.67 2.225 1.214 25.0111 13.15 +1966 9 28 6.45 2.198 1.1543 22.15 13.9111 +1966 9 29 0.13 2.171 1.1842 22.7389 12.5889 +1966 9 30 0 2.144 1.0946 25.2944 7.0222 +1966 10 1 21.37 2.117 1.2339 19.5111 7.3167 +1966 10 2 0.03 2.09 1.622 17.2944 0.0278 +1966 10 3 0 2.063 1.2339 18.6333 1.0389 +1966 10 4 0 2.036 1.0648 24.0667 4.6333 +1966 10 5 0.33 2.01 0.9941 20.3889 8.5167 +1966 10 6 0 1.983 0.9274 18.5611 1.8389 +1966 10 7 0 1.956 0.8856 20.5667 0.3 +1966 10 8 0.04 1.93 0.8677 22.5056 2.0667 +1966 10 9 13.16 1.903 0.8518 20.0667 5.4333 +1966 10 10 0.82 1.877 1.1145 22.9111 11.2611 +1966 10 11 0.08 1.851 1.1543 21.3722 2.4278 +1966 10 12 0.02 1.825 0.9225 22.5778 2.15 +1966 10 13 0 1.799 0.8628 21.8444 1.4556 +1966 10 14 0.1 1.773 0.8428 21.1667 6.0389 +1966 10 15 4.52 1.747 0.8379 19.8611 10.9833 +1966 10 16 2.25 1.722 0.8677 22.4889 10.9444 +1966 10 17 0.16 1.696 0.9404 19.7778 3.4833 +1966 10 18 56.68 1.671 1.0548 13.1 4.5111 +1966 10 19 10.11 1.646 4.4282 12.2056 4.5444 +1966 10 20 0.01 1.621 4.3585 13.9167 2.4333 +1966 10 21 0 1.596 2.3982 15.0167 -1.4333 +1966 10 22 0.01 1.572 1.831 19.4278 1.2889 +1966 10 23 7.87 1.548 1.6121 16.4444 6.45 +1966 10 24 7.48 1.523 1.6618 17.2 9.6389 +1966 10 25 24.2 1.5 1.9006 18.1889 10.1222 +1966 10 26 9.08 1.476 3.8112 14.1278 8.1 +1966 10 27 0.01 1.452 3.5625 17.1 2.8167 +1966 10 28 0.05 1.429 2.5375 20.1944 -0.2889 +1966 10 29 0 1.406 2.0698 21.4389 0.6111 +1966 10 30 0 1.383 1.8409 18.1222 1.7389 +1966 10 31 0 1.361 1.6917 17.9278 -0.05 +1966 11 1 1.66 1.339 1.5922 18.6278 3.3889 +1966 11 2 52.05 1.317 4.1197 14.4333 2.1778 +1966 11 3 0.01 1.295 5.9905 4.8722 -3.6 +1966 11 4 0 1.274 4.2391 10.6222 -6.7167 +1966 11 5 0.02 1.252 2.8758 13.9778 -4.5389 +1966 11 6 0.02 1.232 2.4181 17.9833 0.1722 +1966 11 7 0 1.211 2.1594 18.8222 3.1167 +1966 11 8 0 1.191 1.9802 16.4167 5.5944 +1966 11 9 10.79 1.171 1.8509 15.6833 8.4722 +1966 11 10 29.7 1.151 2.2987 16.5833 11.5167 +1966 11 11 1.6 1.132 4.6173 18.4278 7.5333 +1966 11 12 10.48 1.113 4.2889 19.1611 9.2222 +1966 11 13 0.01 1.094 3.4828 14.6889 5.3833 +1966 11 14 0.02 1.076 2.8559 15.5611 2.6333 +1966 11 15 0 1.058 2.5176 17.8778 -1.2333 +1966 11 16 0 1.04 2.2788 16.3389 -2.55 +1966 11 17 0.02 1.023 2.1096 18.8056 -2.4778 +1966 11 18 0 1.006 1.9902 20.4111 0.7111 +1966 11 19 0.02 0.99 1.8907 17.2167 4.3556 +1966 11 20 0 0.974 1.7912 12.7722 -1.6611 +1966 11 21 2.23 0.958 1.7215 5.4056 -1.55 +1966 11 22 0.02 0.942 1.6817 10.6333 -3.25 +1966 11 23 0 0.927 1.622 15.7278 -4.3111 +1966 11 24 0.01 0.913 1.5623 18.5722 -3.1722 +1966 11 25 0.46 0.898 1.5126 17.4833 -0.2111 +1966 11 26 0.67 0.885 1.5026 18.0944 5.6889 +1966 11 27 10.04 0.871 1.4827 17.1667 7.0889 +1966 11 28 1.71 0.858 1.622 9.6556 -0.6222 +1966 11 29 1.15 0.845 1.5922 0.9833 -4.2167 +1966 11 30 0.05 0.833 1.4628 2.7 -3.4556 +1966 12 1 0.07 0.821 1.4031 10.3 -5.6611 +1966 12 2 0 0.81 1.3732 11.6278 -3.15 +1966 12 3 0.03 0.799 1.3135 7.65 -2.6333 +1966 12 4 0 0.788 1.2538 4.1389 -9.3278 +1966 12 5 0.11 0.778 1.224 5.2944 -7.2444 +1966 12 6 0.06 0.769 1.2339 13.6444 -0.8944 +1966 12 7 1.54 0.759 1.2339 13.2944 6.2778 +1966 12 8 1.45 0.75 1.2339 16.5944 9.7056 +1966 12 9 0.56 0.742 1.2439 17.4222 11.3111 +1966 12 10 29.45 0.734 1.9006 15.7778 9.4278 +1966 12 11 0.01 0.727 3.0749 9.6111 1.0667 +1966 12 12 0.34 0.72 2.2489 5.0667 -0.7667 +1966 12 13 5.84 0.713 1.9504 3.3778 -1.1778 +1966 12 14 0.16 0.707 1.8509 7.2778 -1.7333 +1966 12 15 0 0.701 1.7116 11.0278 -4.8778 +1966 12 16 0 0.696 1.6121 12.5889 -5.8722 +1966 12 17 0.03 0.691 1.5424 10.5833 -4.7722 +1966 12 18 0 0.687 1.5026 11.1389 -2.0444 +1966 12 19 0.02 0.683 1.4727 12.5667 -1.0611 +1966 12 20 0 0.679 1.423 12.3611 -3.1111 +1966 12 21 0.41 0.676 1.3633 13.85 -3.6889 +1966 12 22 0.02 0.674 1.2936 13.7833 -2.0556 +1966 12 23 12.92 0.672 1.3036 8.3611 0.2389 +1966 12 24 1.57 0.67 1.5325 1.1556 -6.8556 +1966 12 25 0.21 0.669 1.4727 1.0778 -11.5278 +1966 12 26 0.85 0.669 1.3533 5.8444 -8.2722 +1966 12 27 0 0.668 1.3135 9.2167 -6.6722 +1966 12 28 32.3 0.669 1.3533 6.0167 -1.6722 +1966 12 29 0.01 0.669 2.9953 4.2278 -3.1222 +1966 12 30 0.06 0.671 2.6768 4.7278 -8.1333 +1966 12 31 1.08 0.672 2.04 4.9222 -3.2833 diff --git a/streamflow/pystreamflow/data/README.md b/streamflow/pystreamflow/data/README.md new file mode 100644 index 0000000..8766b7a --- /dev/null +++ b/streamflow/pystreamflow/data/README.md @@ -0,0 +1,8 @@ +03451500.dly contains the USGS data for the French Broad River at Asheville, North Carolina. + +The data file was obtained from the following Github repository: +https://github.com/Zaijab/DREAM/blob/master/examples/example_9/03451500.dly + +It can be accessed using the load_data function found in load_data.py in the outer directory. + +The file contains tab-separated text with the following columns: year, month, day, precipitation, evaporation, river flow, maximum temperature, and minimum temperature. From ffb9cedd748a26db4d1d0cebd824670ca0652501 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:36:34 +0000 Subject: [PATCH 04/44] add load_data function --- streamflow/pystreamflow/load_data.py | 41 ++++++++++++++++++++++++++++ streamflow/setup.py | 1 + 2 files changed, 42 insertions(+) create mode 100644 streamflow/pystreamflow/load_data.py diff --git a/streamflow/pystreamflow/load_data.py b/streamflow/pystreamflow/load_data.py new file mode 100644 index 0000000..2ec89a5 --- /dev/null +++ b/streamflow/pystreamflow/load_data.py @@ -0,0 +1,41 @@ +"""Function for loading hydrology data. +""" + +import os +import pandas + + +def load_data(station_id): + """Load river data from file. + + This function looks at data files which have been previously saved in the + data directory. + + Parameters + ---------- + station_id : str + The USGS id for the weather station. + 03451500 = French Broad River at Asheville, North Carolina + + Returns + ------- + pandas.DataFrame + The data, with columns names year, month, day, precipitation, + evaporation, streamflow, max_temp, and min_temp. + """ + path = os.path.join( + os.path.dirname(__file__), 'data', '{}.dly'.format(station_id)) + data_file = pandas.read_csv(path, sep='\t', header=None) + + # Add column names + # See https://gist.github.com/josephguillaume/11199609 + data_file.columns = ['year', + 'month', + 'day', + 'precipitation', + 'evaporation', + 'streamflow', + 'max_temp', + 'min_temp'] + + return data_file diff --git a/streamflow/setup.py b/streamflow/setup.py index cacf86c..bab8b3b 100644 --- a/streamflow/setup.py +++ b/streamflow/setup.py @@ -8,6 +8,7 @@ description='Hydrology models in Python and PINTS', version='0.1', install_requires=[ + 'pandas', 'pints', ], extras_require={ From f465408e8d3bb529ce9a454b7684a6b108d7c047 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:40:56 +0000 Subject: [PATCH 05/44] add tests for load data --- streamflow/pystreamflow/__init__.py | 1 + .../pystreamflow/tests/test_load_data.py | 25 +++++++++++++++++++ 2 files changed, 26 insertions(+) create mode 100644 streamflow/pystreamflow/tests/test_load_data.py diff --git a/streamflow/pystreamflow/__init__.py b/streamflow/pystreamflow/__init__.py index 94cd79c..bb7ced2 100644 --- a/streamflow/pystreamflow/__init__.py +++ b/streamflow/pystreamflow/__init__.py @@ -1 +1,2 @@ from .model import * # noqa +from .load_data import * # noqa diff --git a/streamflow/pystreamflow/tests/test_load_data.py b/streamflow/pystreamflow/tests/test_load_data.py new file mode 100644 index 0000000..299312f --- /dev/null +++ b/streamflow/pystreamflow/tests/test_load_data.py @@ -0,0 +1,25 @@ +"""Test the code from load_data.py. +""" + +import unittest +import numpy as np +import pystreamflow + + +class TestLoadData(unittest.TestCase): + + def test_load_data(self): + data = pystreamflow.load_data('03451500') + + # Test that all columns are present + expected_columns = ['year', 'month', 'day', 'precipitation', + 'evaporation', 'streamflow', 'max_temp', + 'min_temp'] + self.assertEqual(list(data.columns), expected_columns) + + # Test the length of the data + self.assertEqual(len(data), 2557) + + # Test that numeric data was loaded into the expected numpy types + self.assertEqual(data.dtypes[0], np.int64) + self.assertEqual(data.dtypes[3], np.float64) From 14160a6097de8726900ef757e5c63800fb4982d8 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 18:45:32 +0000 Subject: [PATCH 06/44] add ode function --- streamflow/pystreamflow/__init__.py | 1 + streamflow/pystreamflow/ode.c | 229 ++++++++++++++++++++ streamflow/pystreamflow/tests/test_model.py | 48 +++- streamflow/setup.py | 6 +- 4 files changed, 280 insertions(+), 4 deletions(-) create mode 100644 streamflow/pystreamflow/ode.c diff --git a/streamflow/pystreamflow/__init__.py b/streamflow/pystreamflow/__init__.py index bb7ced2..e36e473 100644 --- a/streamflow/pystreamflow/__init__.py +++ b/streamflow/pystreamflow/__init__.py @@ -1,2 +1,3 @@ from .model import * # noqa from .load_data import * # noqa +import ode # noqa diff --git a/streamflow/pystreamflow/ode.c b/streamflow/pystreamflow/ode.c new file mode 100644 index 0000000..348ddcb --- /dev/null +++ b/streamflow/pystreamflow/ode.c @@ -0,0 +1,229 @@ +#include +#define _USE_MATH_DEFINES +#include +#include + + +// Flux function +static double +flux_calc(double s, double a) { + double f; + + // Values of s above 1 or below 0 are reset to the most extreme plausible + // value + if (s > 1.0) + s = 1.0; + if (s < 0.0) + s = 0.0; + + // For zero or near-zero a, the flux is linear or near-linear. Use the + // linear approximation, as the flux function is unstable at these + // values. + if (abs(a) <= 0.00001) + return s; + + f = (1 - exp(fmin(600.0, -a * s))) / (1 - exp(fmin(600.0, -a))); + return f; +} + + +// Flux function in Python +static const char flux_docstring[] = \ +"Flux function for hydrological processes.\n" +"\n" +"This is a general function for the relative flux as it depends on relative\n" +"storage and a single shape parameter.\n" +"\n" +"The equation is given by\n" +"\n" +".. math::\n" +" f(S, a) = \\frac{1 - e^{-aS}}{1 - e^{-a}}\n" +"\n" +"To prevent overflow, values of -a*S or -a which exceed 600 will be\n" +"truncated to 600. This limit should not be reached with typical values of a\n" +"and S, but it helps to protect the function during inference if strange\n" +"values are provided by some algorithm. Confer\n" +"https://github.com/Zaijab/DREAM/blob/master/examples/example_14/crr_model.c\n" +"\n" +"Parameters\n" +"----------\n" +"S : float\n" +" Relative storage\n" +"a : float\n" +" Shape parameter\n" +"\n" +"Returns\n" +"-------\n" +"float\n" +" Flux\n"; +static PyObject * +flux(PyObject *self, PyObject *args) { + double s; + double a; + + // read arguments from python + if (!PyArg_ParseTuple(args, "dd", &s, &a)) + return NULL; + + return PyFloat_FromDouble(flux_calc(s, a)); +} + + +// ODE function in Python +static const char ode_rhs_docstring[] = \ +"Evaluate the differential equations.\n" +"\n" +"Parameters\n" +"----------\n" +"t : float\n" +" Time\n" +"y : list\n" +" Current values for [S_i, S_u, S_s, S_f, z]\n" +"precip : float\n" +" Precipitation at this day\n" +"evap : float\n" +" Evaporation at this day\n" +"I_max : float\n" +" maximum interception parameter\n" +"S_umax : float\n" +" unsaturated storage capacity parameter\n" +"Q_smax : float\n" +" maximum percolation parameter\n" +"alpha_e : float\n" +" evaporation flux shape parameter\n" +"alpha_f : float\n" +" runoff flux shape parameter\n" +"K_s : float\n" +" slow reservoir time constant parameter\n" +"K_f : float\n" +" fast reservoir time constant parameter\n" +"alpha_s : float\n" +" percolation flux shape parameter\n" +"alpha_i : float\n" +" interception flux shape parameter\n" +"\n" +"Returns\n" +"-------\n" +"list\n" +" Derivatives for [S_i, S_u, S_s, S_f, z]\n"; +static PyObject * +ode_rhs(PyObject *self, PyObject *args) { + + // variables and model data + double t; + double S_i; + double S_u; + double S_s; + double S_f; + double precip; + double evap; + + // model parameters + double I_max; + double S_umax; + double Q_smax; + double alpha_e; + double alpha_f; + double k_s; + double k_f; + double alpha_s; + double alpha_i; + + // read arguments from python + if (!PyArg_ParseTuple(args, "dddddddddddddddd", &t, &S_i, &S_u, &S_s, &S_f, + &precip, &evap, &I_max, &S_umax, &Q_smax, &alpha_e, &alpha_f, &k_s, &k_f, + &alpha_s, &alpha_i)) + return NULL; + + // temporary variables for calculation of ode function + double intercept_evap; + double effect_precip; + double unsat_evap; + double percolation; + double runoff; + double slow_stream; + double fast_stream; + + // Interception component + intercept_evap = evap * flux_calc(S_i / I_max, alpha_i); + effect_precip = precip * flux_calc(S_i / I_max, -alpha_i); + + // Unsaturated storage + unsat_evap = fmax(0.0, evap - intercept_evap) * flux_calc(S_u / S_umax, alpha_e); + + // Percolation and runoff + percolation = Q_smax * flux_calc(S_u / S_umax, alpha_s); + runoff = effect_precip * flux_calc(S_u / S_umax, alpha_f); + + // Reservoirs + slow_stream = S_s / k_s; + fast_stream = S_f / k_f; + + // Calculate derivatives + double d1; + double d2; + double d3; + double d4; + double d5; + + d1 = precip - intercept_evap - effect_precip; + d2 = effect_precip - unsat_evap - percolation - runoff; + d3 = percolation - slow_stream; + d4 = runoff - fast_stream; + d5 = slow_stream + fast_stream; + + // Return as a python list of floats + return Py_BuildValue("[fffff]", d1, d2, d3, d4, d5); +} + + +// Methods table for python +static PyMethodDef OdeMethods[] = { + {"ode_rhs", ode_rhs, METH_VARARGS, ode_rhs_docstring}, + {"flux", flux, METH_VARARGS, flux_docstring}, + {NULL, NULL, 0, NULL} /* Sentinel */ +}; + + +// Python module +static struct PyModuleDef ode = { + PyModuleDef_HEAD_INIT, + "ode", + NULL, + -1, + OdeMethods +}; + + +PyMODINIT_FUNC +PyInit_ode(void){ + return PyModule_Create(&ode); +} + + +// From https://docs.python.org/3/extending/extending.html +int +main(int argc, char *argv[]) { + wchar_t *program = Py_DecodeLocale(argv[0], NULL); + if (program == NULL) { + fprintf(stderr, "Fatal error: cannot decode argv[0]\n"); + exit(1); + } + + /* Add a built-in module, before Py_Initialize */ + PyImport_AppendInittab("ode", PyInit_ode); + + /* Pass argv[0] to the Python interpreter */ + Py_SetProgramName(program); + + /* Initialize the Python interpreter. Required. */ + Py_Initialize(); + + /* Optionally import the module; alternatively, + import can be deferred until the embedded script + imports it. */ + PyImport_ImportModule("ode"); + + PyMem_RawFree(program); + return 0; +} diff --git a/streamflow/pystreamflow/tests/test_model.py b/streamflow/pystreamflow/tests/test_model.py index fe384b0..cbbfa42 100644 --- a/streamflow/pystreamflow/tests/test_model.py +++ b/streamflow/pystreamflow/tests/test_model.py @@ -1,4 +1,4 @@ -"""Test the code from model.py. +"""Test the code from model.py and ode.c. """ import math @@ -13,12 +13,54 @@ def test_flux(self): a = 2.0 s = 0.5 expected = (1 - math.exp(-a * s)) / (1 - math.exp(-a)) - f = pystreamflow.flux(s, a) + f = pystreamflow.ode.flux(s, a) self.assertAlmostEqual(f, expected) # Test with near zero value of a a = 1e-20 s = 0.5 expected = 0.5 - f = pystreamflow.flux(s, a) + f = pystreamflow.ode.flux(s, a) self.assertAlmostEqual(f, expected) + + +class TestRHS(unittest.TestCase): + + def test_rhs(self): + # Test the ode function + params = [2.5, 100, 7, 1, -0.5, 60, 3.25, 0, 50] + + # Test with completely dry conditions. There should be no change in any + # component + y = [0.0] * 4 + f = pystreamflow.ode.ode_rhs(0, *y, 0, 1.0, *params) + self.assertEqual(f, [0.0] * 5) + self.assertGreaterEqual(f[4], 0.0) + + # Test that precipitation enters the interception component + f = pystreamflow.ode.ode_rhs(0, *y, 10.0, 1.0, *params) + self.assertAlmostEqual(f[0], 10.0) + self.assertGreaterEqual(f[4], 0.0) + + # Test that with full interception storage, all precipitation enters + # unsaturated storage + y = [2.5, 0.0, 0.0, 0.0] + f = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params) + self.assertAlmostEqual(f[1], 5.0) + self.assertGreaterEqual(f[4], 0.0) + + # Test effect of slow time constant + y = [0.5] * 4 + params1 = [2.5, 100, 7, 1, -0.5, 10, 3.25, 0, 50] + params2 = [2.5, 100, 7, 1, -0.5, 1000, 3.25, 0, 50] + f1 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params1) + f2 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params2) + self.assertGreaterEqual(f2[2], f1[2]) + + # Test effect of fast time constant + y = [0.5] * 4 + params1 = [2.5, 100, 7, 1, -0.5, 10, 3.2, 0, 50] + params2 = [2.5, 100, 7, 1, -0.5, 10, 32.0, 0, 50] + f1 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params1) + f2 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params2) + self.assertGreaterEqual(f2[3], f1[3]) diff --git a/streamflow/setup.py b/streamflow/setup.py index bab8b3b..157efa8 100644 --- a/streamflow/setup.py +++ b/streamflow/setup.py @@ -1,7 +1,10 @@ """Setup script for the pystreamflow python package. """ -from setuptools import setup +import os +from setuptools import setup, Extension + +ext1 = Extension('ode', [os.path.join('pystreamflow', 'ode.c')]) setup( name='pystreamflow', @@ -16,4 +19,5 @@ 'flake8>=3', ] }, + ext_modules=[ext1], ) From 091ef16c9875707dd8f5e0dc448d5da875ef02ad Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:18:26 +0000 Subject: [PATCH 07/44] add new forward model --- streamflow/pystreamflow/model.py | 288 ++++++++++++++++++-- streamflow/pystreamflow/tests/test_model.py | 62 +++++ 2 files changed, 322 insertions(+), 28 deletions(-) diff --git a/streamflow/pystreamflow/model.py b/streamflow/pystreamflow/model.py index 3c94af5..9d59cf6 100644 --- a/streamflow/pystreamflow/model.py +++ b/streamflow/pystreamflow/model.py @@ -2,41 +2,273 @@ """ import math +import numpy as np +import scipy.integrate +import pints +import pystreamflow +# Try to import the optional scikit odes solver, and record whether or not it +# was available +try: + import scikits.odes + scikit_ode_avail = True +except ImportError: + scikit_ode_avail = False -def flux(S, a): - r"""Flux function for hydrological processes. - This is a general function for the relative flux as it depends on relative - storage and a single shape parameter. +class RiverModel(pints.ForwardModel): + """Rainfall runoff model of river streamflow. - The equation is given by + The model has four latent state variables: - .. math:: - f(S, a) = \frac{1 - e^{-aS}}{1 - e^{-a}} + S_i = interception storage + S_u = unsaturated storage + S_s = slow reservoir + S_f = fast reservoir - To prevent overflow, values of -a*S or -a which exceed 600 will be - truncated to 600. This limit should not be reached with typical values of a - and S, but it helps to protect the function during inference if strange - values are provided by some algorithm. Confer - https://github.com/Zaijab/DREAM/blob/master/examples/example_14/crr_model.c + and one observed variable: - Parameters + z = water flowed out of the river + + (In fact, it is dz/dt, or the streamflow, that is observed.) + + The model is characterized by the following unknown parameters: + + I_max = maximum interception + S_u,max = unsaturated storage capacity + Q_s,max = maximum percolation + alpha_e = evaporation flux shape + alpha_f = runoff flux shape + K_s = slow reservoir time constant + K_f = fast reservoir time constant + + as well as the following two parameters whose values are here assumed fixed + and known: + + alpha_s = 0 (percolation flux shape) + alpha_i = 50 (interception flux shape) + + Appearing multiple times in the model is the flux function f, given by: + + f(S, a) = (1 - exp(-a * S)) / (1 - exp(-a)) + + The behavior of all the variables is governed by a system of differential + equations, namely + + dS_i/dt = Precip(t) - InterceptEvap(t) - EffectPrecip(t) + dS_u/dt = EffectPrecip(t) - UnsatEvap(t) - Percolation(t) - Runoff(t) + dS_s/dt = Percolation(t) - SlowStream(t) + dS_f/dt = Runoff(t) - FastStream(t) + dz/dt = SlowStream(t) + FastStream(t) + + Each term is defined below. + + Precip = measured precipitation (provided as input to the model) + + Evap = measured or theoretical evaporation (provided as input to the model) + + InterceptEvap = evaporation from the interception component + InterceptEvap(t) = Evap(t) * f(S_i / I_max, alpha_i) + + EffectPrecip = effective precipitation that gets sent to unsaturated + storage + EffectPrecip(t) = Precip(t) * f(S_i / I_max, -alpha_i) + + UnsatEvap = evaporation from unsaturated storage + UnsatEvap(t) = max(0, Evap(t) - InterceptEvap(t)) + * f(S_u / S_u,max, alpha_e) + + Percolation = trickling of water through the ground + Percolation(t) = Q_s,max * f(S_u / S_u,max, alpha_s) + + Runoff = flow of water on the surface + Runoff(t) = EffectPrecip(t) * f(S_u / S_u,max, alpha_f) + + SlowStream = The slow component of the river flow + SlowStream(t) = S_s / K_s + + FastStream = The fast component of the river flow + FastStream(t) = S_f / K_f + + Models of this type are described in [1]_ and [2]_. + See also the following MATLAB code + https://github.com/Zaijab/DREAM/tree/master/examples/example_14 + + References ---------- - S : float - Relative storage - a : float - Shape parameter - - Returns - ------- - float - Flux + .. [1] Schoups, G., & Vrugt, J. A. (2010). A formal likelihood function for + parameter and predictive inference of hydrologic models with + correlated, heteroscedastic, and non‐Gaussian errors. Water + Resources Research, 46(10). + .. [2] Schoups, G., Vrugt, J. A., Fenicia, F., & van de Giesen, N. C. + (2010). Inaccurate numerical implementation of conceptual hydrologic + models corrupts accuracy and efficiency of MCMC simulation. Water + Resources Research, 46, W10530. """ - if abs(a) <= 1e-6: - # For zero or near-zero a, the flux is linear or near-linear. Use the - # linear approximation, as the flux function is unstable at these - # values. - return S + def __init__(self, + times, + rainfall, + evaporation, + solver='scipy', + rtol=1e-7, + atol=1e-7): + """ + Parameters + ---------- + times : list + Time points corresponding to the rainfall and evaporation data + rainfall : list + Daily rainfall measurements + evaporation : list + Daily evaporation measurements + solver : {'scipy', 'scikit'}, optional ('scipy') + Which ODE solver library to use. 'scipy' corresponds to the + scipy.integrate.solve_ivp function. 'scikit' uses scikits.odes. + Note that scikits.odes is an optional dependency which must be + available for this option to work. + rtol : float + Relative tolerance for the ODE solver + atol : float + Absolute tolerance for the ODE solver + """ + super().__init__() + + self.set_model_data(times, rainfall, evaporation) + + # Initial conditions + # Set all the variables to a small value. To eliminate the effect of + # the initial condition, the model should be run for some time before + # comparing its output to data. + S_i = 1e-6 + S_u = 1e-6 + S_s = 1e-6 + S_f = 1e-6 + z = 1e-6 + self.init_cond = [S_i, S_u, S_s, S_f, z] + + # Solver properties + self.solver = solver + self.rtol = rtol + self.atol = atol + + # Check that scikit is available + if self.solver == 'scikit' and not scikit_ode_avail: + raise RuntimeError('scikit solver could not be imported') + + def n_parameters(self): + return 7 + + def set_model_data(self, times, rainfall, evaporation): + """Set the rainfall and evaporation data. + + Parameters + ---------- + times : list + Time points corresponding to the rainfall and evaporation data + rainfall : list + Daily rainfall measurements + evaporation : list + Daily evaporation measurements + """ + self.model_data_times = times + self.rainfall_data = rainfall + self.evap_data = evaporation + + def simulate(self, parameters, times): + """Run a forward simulation. + + It uses the rainfall and evaporation data saved inside this model + object. + + Parameters + ---------- + parameters : list + [I_max, S_umax, Q_smax, alpha_e, alpha_f, K_s, K_f] + times : list + Time points on which to evaluate the solution + + Returns + ------- + np.array + Solution for river streamflow at the given times and parameters + """ + # Check that the time range has data + if min(times) < min(self.model_data_times) or \ + max(times) > max(self.model_data_times): + raise RuntimeError('Rainfall and evaporation data are not ' + 'available at these time points.') + + # Set values for fixed parameters + alpha_s = 0.0 + alpha_i = 50 + + # Get the starting day for model data + first_model_data_time = min(self.model_data_times) + + if self.solver == 'scipy': + # Define derivative function for solver + def f(t, y): + index = math.floor(t - first_model_data_time) + 1 + precip = self.rainfall_data[index] + evap = self.evap_data[index] + return pystreamflow.ode.ode_rhs( + t, + *y[:-1], + precip, + evap, + *parameters, + alpha_s, + alpha_i) + + # Solve the equation + t_range = (min(first_model_data_time, min(times)), max(times)) + res = scipy.integrate.solve_ivp( + f, + t_range, + self.init_cond, + t_eval=[times[0]-1] + list(times), + rtol=self.rtol, + atol=self.atol, + method='RK23' + ) + + # Get the flow component + y = list(res.y[4]) + + elif self.solver == 'scikit': + # Define derivative function for solver + def f(t, y, ydot): + index = math.floor(t - first_model_data_time) + 1 + precip = self.rainfall_data[index] + evap = self.evap_data[index] + d = pystreamflow.ode.ode_rhs( + t, + *y[:-1], + precip, + evap, + *parameters, + alpha_s, + alpha_i) + + ydot[0] = d[0] + ydot[1] = d[1] + ydot[2] = d[2] + ydot[3] = d[3] + ydot[4] = d[4] + + t_eval = list(np.arange(0, times[0])) + list(times) + solution = scikits.odes.ode( + 'cvode', + f, + old_api=False, + rtol=self.rtol, + atol=self.atol) + + solution = solution.solve(t_eval, self.init_cond) + + y = solution.values.y[-len(times)-1:, 4] + + # Take the difference, which corresponds to the measurements (flow) + y = np.diff(y) - return (1 - math.exp(min(600, -a * S))) / (1 - math.exp(min(600, -a))) + return y diff --git a/streamflow/pystreamflow/tests/test_model.py b/streamflow/pystreamflow/tests/test_model.py index cbbfa42..98619a5 100644 --- a/streamflow/pystreamflow/tests/test_model.py +++ b/streamflow/pystreamflow/tests/test_model.py @@ -2,10 +2,14 @@ """ import math +from importlib import reload +import sys import unittest +import unittest.mock import pystreamflow + class TestFlux(unittest.TestCase): def test_flux(self): @@ -64,3 +68,61 @@ def test_rhs(self): f1 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params1) f2 = pystreamflow.ode.ode_rhs(0, *y, 5.0, 1.0, *params2) self.assertGreaterEqual(f2[3], f1[3]) + + +class TestRiverModel(unittest.TestCase): + + @classmethod + def setUpClass(cls): + cls.input_times = [1, 2, 3, 4, 5, 6, 7] + cls.precip = [0, 10, 0, 20, 20, 0, 1] + cls.evap = [3, 3.5, 4, 4.5, 5, 5.5, 5.5] + + def test_init(self): + # Test initialization + pystreamflow.RiverModel(self.input_times, self.precip, self.evap) + + def test_n_parameters(self): + m = pystreamflow.RiverModel(self.input_times, self.precip, self.evap) + self.assertEqual(m.n_parameters(), 7) + + def test_set_model_data(self): + m = pystreamflow.RiverModel(self.input_times, self.precip, self.evap) + + self.assertEqual(m.model_data_times, self.input_times) + self.assertEqual(m.rainfall_data, self.precip) + self.assertEqual(m.evap_data, self.evap) + + def test_simulate(self): + # Test running simulate + params = [2.5, 100, 7, 1, -0.5, 60, 3.25] + times = [4, 5, 6] + m = pystreamflow.RiverModel(self.input_times, self.precip, self.evap) + y = m.simulate(params, times) + self.assertEqual(len(y), 3) + + m = pystreamflow.RiverModel( + self.input_times, self.precip, self.evap, solver='scikit') + y = m.simulate(params, times) + self.assertEqual(len(y), 3) + + def test_no_data(self): + # Test trying to simulate where data has not been provided + params = [2.5, 100, 7, 1, -0.5, 60, 3.25] + times = [10, 11, 12] + m = pystreamflow.RiverModel(self.input_times, self.precip, self.evap) + + with self.assertRaises(RuntimeError) as e: + m.simulate(params, times) + self.assertTrue('data are not available' in str(e.exception)) + + def test_solvers(self): + # Test when the scikit solver is not available + with unittest.mock.patch.dict(sys.modules): + sys.modules['scikits.odes'] = None + reload(sys.modules['pystreamflow.model']) + + with self.assertRaises(RuntimeError) as e: + pystreamflow.RiverModel( + self.input_times, self.precip, self.evap, solver='scikit') + self.assertTrue('scikit solver could not be' in str(e.exception)) From e27282a2565aff3299290ec232d3dc1da28fad42 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:23:07 +0000 Subject: [PATCH 08/44] add script to run model --- streamflow/pystreamflow/run_inference.py | 133 ++++++++++++++++++++ streamflow/pystreamflow/tests/test_model.py | 1 - 2 files changed, 133 insertions(+), 1 deletion(-) create mode 100644 streamflow/pystreamflow/run_inference.py diff --git a/streamflow/pystreamflow/run_inference.py b/streamflow/pystreamflow/run_inference.py new file mode 100644 index 0000000..a369105 --- /dev/null +++ b/streamflow/pystreamflow/run_inference.py @@ -0,0 +1,133 @@ +"""Script for running the model. +""" + +import numpy as np +import matplotlib.pyplot as plt +import pints +import pints.plot +import pystreamflow + + +def run_inference(optimize=False): + # Load data and model + data = pystreamflow.load_data('03451500') + + precip = data['precipitation'].to_numpy()[365:] + evap = data['evaporation'].to_numpy()[365:] + flow = data['streamflow'].to_numpy()[365:] + all_times = np.arange(len(precip)) + m = pystreamflow.RiverModel(all_times, precip, evap, solver='scikit') + + # Time range for data + data_times = all_times[730:1095] + data_flow = flow[730:1095] + + # Build prior + I_max_prior = pints.UniformLogPrior(0, 10) + S_umax_prior = pints.UniformLogPrior(10, 1000) + Q_smax_prior = pints.UniformLogPrior(0, 100) + alpha_e_prior = pints.UniformLogPrior(0, 100) + alpha_f_prior = pints.UniformLogPrior(-10, 10) + K_s_prior = pints.UniformLogPrior(0, 150) + K_f_prior = pints.UniformLogPrior(0, 10) + sigma_prior = pints.UniformLogPrior(0, 1e6) + + # Good parameter values + params = [9.0, 200.0, 7.0, 85.0, 0.2, 70.0, 2.5, 1.0] + + # Make objects for pints + problem = pints.SingleOutputProblem(m, data_times, data_flow) + likelihood = pints.GaussianLogLikelihood(problem) + prior = pints.ComposedLogPrior( + I_max_prior, + S_umax_prior, + Q_smax_prior, + alpha_e_prior, + alpha_f_prior, + K_s_prior, + K_f_prior, + sigma_prior + ) + posterior = pints.LogPosterior(likelihood, prior) + + if optimize: + opt = pints.OptimisationController( + posterior, params, method=pints.SNES) + opt.set_parallel(True) + opt.set_max_iterations(10) + p, _ = opt.run() + p = params + + # Plot results + y = m.simulate(p[:-1], data_times) + fig = plt.figure() + ax = fig.add_subplot(1, 1, 1) + ax.plot(data_times, y, label='Fit') + ax.plot( + data_times, data_flow, 'x-', label='Data', color='k', alpha=0.5) + ax.set_xlabel('Time (days)') + ax.legend() + plt.show() + + else: + mcmc = pints.MCMCController( + posterior, 6, [params]*6, method=pints.DreamMCMC) + mcmc.set_max_iterations(10) + mcmc.set_parallel(True) + chains = mcmc.run() + + pints.plot.trace(chains) + plt.show() + + pints.plot.pairwise(chains[0, :, :], kde=True) + plt.show() + + +def plot_likelihood(): + # Load data and model + data = pystreamflow.load_data('03451500') + + precip = data['precipitation'].to_numpy()[365:] + evap = data['evaporation'].to_numpy()[365:] + flow = data['streamflow'].to_numpy()[365:] + all_times = np.arange(len(precip)) + m = pystreamflow.RiverModel( + all_times, precip, evap, solver='scipy', rtol=1e-3, atol=1e-3) + m_accurate = pystreamflow.RiverModel( + all_times, precip, evap, solver='scikit') + + # Time range for data + data_times = all_times[730:1095] + data_flow = flow[730:1095] + + # Make objects for pints + problem = pints.SingleOutputProblem(m, data_times, data_flow) + likelihood = pints.GaussianLogLikelihood(problem) + + problem_accurate = pints.SingleOutputProblem( + m_accurate, data_times, data_flow) + likelihood_accurate = pints.GaussianLogLikelihood(problem_accurate) + + # Other parameters + params = [9.0, 200.0, 7.0, 85.0, 0.2, 70.0, 2.5, 1.0] + + # Get a slice of the likelihood + q_range = np.linspace(6.0, 10.0, 50) + lls = [] + lls_accurate = [] + for q in q_range: + params[2] = q + lls.append(likelihood(params)) + lls_accurate.append(likelihood_accurate(params)) + + plt.plot(q_range, lls, label='RK23 tol=1e-3') + plt.plot(q_range, lls_accurate, label='CVODE tol=1e-7') + plt.legend() + plt.xlabel('Q_s,max') + plt.ylabel('Log likelihood') + plt.show() + + +if __name__ == '__main__': + plot_likelihood() + run_inference(optimize=False) diff --git a/streamflow/pystreamflow/tests/test_model.py b/streamflow/pystreamflow/tests/test_model.py index 98619a5..3bed31e 100644 --- a/streamflow/pystreamflow/tests/test_model.py +++ b/streamflow/pystreamflow/tests/test_model.py @@ -9,7 +9,6 @@ import pystreamflow - class TestFlux(unittest.TestCase): def test_flux(self): From 06b316c9dd8d16b009e7efe28067e95f25efa509 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:25:30 +0000 Subject: [PATCH 09/44] add dependencies to setup --- streamflow/setup.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/streamflow/setup.py b/streamflow/setup.py index 157efa8..90dbbff 100644 --- a/streamflow/setup.py +++ b/streamflow/setup.py @@ -11,13 +11,19 @@ description='Hydrology models in Python and PINTS', version='0.1', install_requires=[ + 'numpy', + 'scipy', + 'matplotlib', 'pandas', 'pints', ], extras_require={ 'dev': [ 'flake8>=3', - ] + ], + 'cvode': [ + 'scikits.odes', + ], }, ext_modules=[ext1], ) From 9a4dfed072d79ef1866726d7273931a93e02c7ff Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:33:07 +0000 Subject: [PATCH 10/44] add sundials to actions --- .github/workflows/install_dependencies.sh | 7 +++++++ .github/workflows/unit-python-ver-test.yml | 4 ++++ 2 files changed, 11 insertions(+) create mode 100644 .github/workflows/install_dependencies.sh diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh new file mode 100644 index 0000000..78f5f06 --- /dev/null +++ b/.github/workflows/install_dependencies.sh @@ -0,0 +1,7 @@ +#!/bin/bash + +# Update apt-get +apt-get -qq update; + +# Install Sundials (for CVODE) +apt-get install -y libsundials-dev; diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 2768aaa..00da29f 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -32,6 +32,10 @@ jobs: python-version: ${{ matrix.python-version }} architecture: x64 + - name: Install dependencies + run: | + sudo ./.github/workflows/install_dependencies.sh + - name: Install models run: | python --version From d147afdc50ca8d568f1328ba2006bad0dfe3ff2a Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:39:56 +0000 Subject: [PATCH 11/44] install extras in unit tests --- .github/workflows/unit-python-ver-test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 00da29f..77b02d6 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -41,7 +41,7 @@ jobs: python --version python -m pip install --upgrade pip setuptools wheel python -m pip install -e ./streamflow/ - python -m pip install -e ./streamflow/[dev] + python -m pip install -e ./streamflow/[dev,cvode] - name: run unit tests run: | From 1eb4a65d20c0bb6e97b6e8ed3b2456045aba512e Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:48:20 +0000 Subject: [PATCH 12/44] try install again --- .github/workflows/install_dependencies.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) mode change 100644 => 100755 .github/workflows/install_dependencies.sh diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh old mode 100644 new mode 100755 From b2b1c6979601dabaf7c6716695ced25f16478fd1 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 19:58:47 +0000 Subject: [PATCH 13/44] add blas and lapack --- .github/workflows/install_dependencies.sh | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 78f5f06..0964f27 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -4,4 +4,5 @@ apt-get -qq update; # Install Sundials (for CVODE) +apt-get install libopenblas-dev liblapack-dev apt-get install -y libsundials-dev; From bb9a72819d36bef6451d0f5c1f695a0903d31c42 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:07:15 +0000 Subject: [PATCH 14/44] add ubuntu dependencies --- .github/workflows/install_dependencies.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 0964f27..7c043b0 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -4,5 +4,5 @@ apt-get -qq update; # Install Sundials (for CVODE) -apt-get install libopenblas-dev liblapack-dev +apt-get install libopenblas-dev liblapack-dev libatlas-base-dev gfortran intel-mkl-2019.4-070 apt-get install -y libsundials-dev; From 73c6c038b62a187249d613a8d8ffad7ff4204d2d Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:13:16 +0000 Subject: [PATCH 15/44] remove failing installs --- .github/workflows/install_dependencies.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 7c043b0..80b3a42 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -4,5 +4,5 @@ apt-get -qq update; # Install Sundials (for CVODE) -apt-get install libopenblas-dev liblapack-dev libatlas-base-dev gfortran intel-mkl-2019.4-070 +apt-get install libopenblas-dev liblapack-dev intel-mkl-2019.4-070 apt-get install -y libsundials-dev; From 7e3fb8c9188cb87967a4b1ad6532f3ac8830b560 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:17:03 +0000 Subject: [PATCH 16/44] remove mkl --- .github/workflows/install_dependencies.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 80b3a42..0964f27 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -4,5 +4,5 @@ apt-get -qq update; # Install Sundials (for CVODE) -apt-get install libopenblas-dev liblapack-dev intel-mkl-2019.4-070 +apt-get install libopenblas-dev liblapack-dev apt-get install -y libsundials-dev; From 122db4a82b4f4df466054390a0eb5577da67b7da Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:31:57 +0000 Subject: [PATCH 17/44] switch to sundials v5 --- .github/workflows/install_dependencies.sh | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 0964f27..48096eb 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -4,5 +4,10 @@ apt-get -qq update; # Install Sundials (for CVODE) -apt-get install libopenblas-dev liblapack-dev -apt-get install -y libsundials-dev; +apt-get install -y libopenblas-dev liblapack-dev +wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.tar.gz +tar xzf sundials-5.1.0.tar.gz +mkdir build-sundials-5.1.0 +cd build-sundials-5.1.0/ +cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=/usr/local/ ../sundials-5.1.0/ +make install From 6f1bc2ca6e2bd01bfcd621ebde8bd950e3e839c7 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:39:58 +0000 Subject: [PATCH 18/44] export paths --- .github/workflows/install_dependencies.sh | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 48096eb..a70c820 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -11,3 +11,5 @@ mkdir build-sundials-5.1.0 cd build-sundials-5.1.0/ cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=/usr/local/ ../sundials-5.1.0/ make install +export SUNDIALS_INST=/usr/local/ +export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH From e00907ada6d5174d93f1f1380a0ab18a82633f8a Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 20:49:43 +0000 Subject: [PATCH 19/44] remove unusual install path --- .github/workflows/install_dependencies.sh | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index a70c820..e97cd79 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -9,7 +9,5 @@ wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.ta tar xzf sundials-5.1.0.tar.gz mkdir build-sundials-5.1.0 cd build-sundials-5.1.0/ -cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=/usr/local/ ../sundials-5.1.0/ +cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ make install -export SUNDIALS_INST=/usr/local/ -export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH From cbcc6a65672b833a20a184a6a799fba532abab77 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:00:21 +0000 Subject: [PATCH 20/44] add ld library path --- .github/workflows/install_dependencies.sh | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index e97cd79..8ebca86 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -11,3 +11,4 @@ mkdir build-sundials-5.1.0 cd build-sundials-5.1.0/ cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ make install +export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH From cb7f1e288d6143e5be47dcba6541f16b50899bb2 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:08:41 +0000 Subject: [PATCH 21/44] use github env variables --- .github/workflows/install_dependencies.sh | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index 8ebca86..a7730de 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -9,6 +9,7 @@ wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.ta tar xzf sundials-5.1.0.tar.gz mkdir build-sundials-5.1.0 cd build-sundials-5.1.0/ -cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ +cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=$GITHUB_WORKSPACE ../sundials-5.1.0/ make install -export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH +export SUNDIALS_INST=$GITHUB_WORKSPACE +export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH From 6df1ee0a41b2db256b724caff2fb8a9bd058933c Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:14:12 +0000 Subject: [PATCH 22/44] remove path from cmake --- .github/workflows/install_dependencies.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh index a7730de..1eab16e 100755 --- a/.github/workflows/install_dependencies.sh +++ b/.github/workflows/install_dependencies.sh @@ -9,7 +9,7 @@ wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.ta tar xzf sundials-5.1.0.tar.gz mkdir build-sundials-5.1.0 cd build-sundials-5.1.0/ -cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=$GITHUB_WORKSPACE ../sundials-5.1.0/ +cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ make install export SUNDIALS_INST=$GITHUB_WORKSPACE export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH From a81fb72645f0fde5b2327a38bb5b0c9cafb582d1 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:24:15 +0000 Subject: [PATCH 23/44] print paths --- .github/workflows/unit-python-ver-test.yml | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 77b02d6..c6141d6 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -36,6 +36,12 @@ jobs: run: | sudo ./.github/workflows/install_dependencies.sh + - name: print + run: | + echo $GITHUB_WORKSPACE + echo $LD_LIBRARY_PATH + echo $SUNDIALS_INST + - name: Install models run: | python --version From f725c311c569f5d3ec18568db3923f74606b281b Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:30:40 +0000 Subject: [PATCH 24/44] print paths --- .github/workflows/unit-python-ver-test.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index c6141d6..6b9a848 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -38,6 +38,8 @@ jobs: - name: print run: | + export SUNDIALS_INST=/usr/local + export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH echo $GITHUB_WORKSPACE echo $LD_LIBRARY_PATH echo $SUNDIALS_INST From 9ac6746e2e2ae5625a68de8c40a0c4b16f55b8f7 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:40:22 +0000 Subject: [PATCH 25/44] move install to yml --- .github/workflows/unit-python-ver-test.yml | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 6b9a848..d969e68 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -32,14 +32,25 @@ jobs: python-version: ${{ matrix.python-version }} architecture: x64 + # - name: Install dependencies + # run: | + # sudo ./.github/workflows/install_dependencies.sh + - name: Install dependencies run: | - sudo ./.github/workflows/install_dependencies.sh + apt-get -qq update; + apt-get install -y libopenblas-dev liblapack-dev + wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.tar.gz + tar xzf sundials-5.1.0.tar.gz + mkdir build-sundials-5.1.0 + cd build-sundials-5.1.0/ + cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 -DCMAKE_INSTALL_PREFIX=$GITHUB_WORKSPACE ../sundials-5.1.0/ + make install + export SUNDIALS_INST=$GITHUB_WORKSPACE + export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH - name: print run: | - export SUNDIALS_INST=/usr/local - export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH echo $GITHUB_WORKSPACE echo $LD_LIBRARY_PATH echo $SUNDIALS_INST From d1a69a2308e5b59aa0c40923015ca77608bde204 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:41:55 +0000 Subject: [PATCH 26/44] add sudo --- .github/workflows/unit-python-ver-test.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index d969e68..54bd875 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -38,8 +38,8 @@ jobs: - name: Install dependencies run: | - apt-get -qq update; - apt-get install -y libopenblas-dev liblapack-dev + sudo apt-get -qq update; + sudo apt-get install -y libopenblas-dev liblapack-dev wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.tar.gz tar xzf sundials-5.1.0.tar.gz mkdir build-sundials-5.1.0 From 99eaa7e2447e33169e818b3d5dc642a0dd25e7f0 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:47:01 +0000 Subject: [PATCH 27/44] repeat export --- .github/workflows/unit-python-ver-test.yml | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 54bd875..21ae654 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -51,12 +51,16 @@ jobs: - name: print run: | + export SUNDIALS_INST=$GITHUB_WORKSPACE + export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH echo $GITHUB_WORKSPACE echo $LD_LIBRARY_PATH echo $SUNDIALS_INST - name: Install models run: | + export SUNDIALS_INST=$GITHUB_WORKSPACE + export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH python --version python -m pip install --upgrade pip setuptools wheel python -m pip install -e ./streamflow/ @@ -64,4 +68,6 @@ jobs: - name: run unit tests run: | + export SUNDIALS_INST=$GITHUB_WORKSPACE + export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH python run-tests.py --unit From 7f72b4e395c6152758c75cefbc027ff84eadb22f Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Thu, 25 Mar 2021 21:52:40 +0000 Subject: [PATCH 28/44] remove print and unused sh --- .github/workflows/install_dependencies.sh | 15 --------------- .github/workflows/unit-python-ver-test.yml | 12 ------------ 2 files changed, 27 deletions(-) delete mode 100755 .github/workflows/install_dependencies.sh diff --git a/.github/workflows/install_dependencies.sh b/.github/workflows/install_dependencies.sh deleted file mode 100755 index 1eab16e..0000000 --- a/.github/workflows/install_dependencies.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash - -# Update apt-get -apt-get -qq update; - -# Install Sundials (for CVODE) -apt-get install -y libopenblas-dev liblapack-dev -wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.tar.gz -tar xzf sundials-5.1.0.tar.gz -mkdir build-sundials-5.1.0 -cd build-sundials-5.1.0/ -cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ -make install -export SUNDIALS_INST=$GITHUB_WORKSPACE -export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index 21ae654..d35fb25 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -32,10 +32,6 @@ jobs: python-version: ${{ matrix.python-version }} architecture: x64 - # - name: Install dependencies - # run: | - # sudo ./.github/workflows/install_dependencies.sh - - name: Install dependencies run: | sudo apt-get -qq update; @@ -49,14 +45,6 @@ jobs: export SUNDIALS_INST=$GITHUB_WORKSPACE export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH - - name: print - run: | - export SUNDIALS_INST=$GITHUB_WORKSPACE - export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/lib:$LD_LIBRARY_PATH - echo $GITHUB_WORKSPACE - echo $LD_LIBRARY_PATH - echo $SUNDIALS_INST - - name: Install models run: | export SUNDIALS_INST=$GITHUB_WORKSPACE From 9499184a09f7b0fd231a06789271fc8d23627458 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Fri, 26 Mar 2021 11:36:27 +0000 Subject: [PATCH 29/44] write model readme --- streamflow/README.md | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) diff --git a/streamflow/README.md b/streamflow/README.md index 334fa30..7e9dfd0 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -1 +1,37 @@ +# pystreamflow + pystreamflow enables efficient simulation and inference for rainfall runoff differential equation models of the sort that arise in hydrological modelling of river basins. + +## Installation + +1. Navigate to `differential-equations-inference-db/streamflow/` (this directory) +1. For a simple install, run `pip install .` +1. To install with support for the CVODE solver via scikits.odes, run `pip install .[cvode]` + +### Installing with CVODE + +The CVODE solver enables faster model evaluations and inference, but it requires you to install the SUNDIALS C library and the scikits.odes Python package. The following is a typical install process for the 5.1.0 version of SUNDIALS: + +``` +sudo apt-get install libopenblas-dev liblapack-dev +wget https://github.com/LLNL/sundials/releases/download/v5.1.0/sundials-5.1.0.tar.gz +tar xzf sundials-5.1.0.tar.gz +mkdir build-sundials-5.1.0 +cd build-sundials-5.1.0/ +cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ +make install +``` + +scikits.odes is pip installable, but it is often necessary to refer to its [installation documentation](https://scikits-odes.readthedocs.io/en/latest/installation.html), which contains troubleshooting information. + +If you have conda, an alternative is to use conda forge: + +``` +conda install -c conda-forge scikits.odes +``` + +## Usage + +Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). + +Refer to the notebook in the examples directory for typical usage. From 6e4b9e850c38485d6c46e91130706baa3e9c1405 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 29 Mar 2021 09:20:47 +0100 Subject: [PATCH 30/44] upload notebook --- streamflow/examples/data_and_inference.ipynb | 1701 ++++++++++++++++++ 1 file changed, 1701 insertions(+) create mode 100644 streamflow/examples/data_and_inference.ipynb diff --git a/streamflow/examples/data_and_inference.ipynb b/streamflow/examples/data_and_inference.ipynb new file mode 100644 index 0000000..272de77 --- /dev/null +++ b/streamflow/examples/data_and_inference.ipynb @@ -0,0 +1,1701 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "silent-adaptation", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pandas\n", + "import pints\n", + "import pints.plot\n", + "import pystreamflow" + ] + }, + { + "cell_type": "markdown", + "id": "supported-terrorism", + "metadata": {}, + "source": [ + "# pystreamflow example notebook\n", + "\n", + "This notebook demonstrates the model and data in the pystreamflow package." + ] + }, + { + "cell_type": "markdown", + "id": "first-horizontal", + "metadata": {}, + "source": [ + "The package includes river data for the French Broad River at Asheville, North Carolina (USGS station 03451500).\n", + "\n", + "This data can be loaded using the `load_data` function in pystreamflow, which returns a pandas dataframe." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "pregnant-return", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " year month day precipitation evaporation streamflow max_temp \\\n", + "0 1960 1 1 0.00 0.670 1.8907 1.7667 \n", + "1 1960 1 2 14.53 0.680 1.8210 6.0778 \n", + "2 1960 1 3 7.51 0.683 2.7863 9.3833 \n", + "3 1960 1 4 0.29 0.687 3.2540 4.5056 \n", + "4 1960 1 5 17.23 0.692 2.6072 3.9889 \n", + "5 1960 1 6 7.68 0.697 3.3535 4.3167 \n", + "6 1960 1 7 4.03 0.702 3.4331 7.3889 \n", + "7 1960 1 8 0.01 0.708 3.0450 10.9000 \n", + "8 1960 1 9 0.00 0.714 2.6868 14.6222 \n", + "9 1960 1 10 0.01 0.721 2.4479 16.2944 \n", + "\n", + " min_temp \n", + "0 -7.2500 \n", + "1 -3.1667 \n", + "2 0.2667 \n", + "3 -3.6389 \n", + "4 -1.3778 \n", + "5 -0.5667 \n", + "6 0.8500 \n", + "7 -2.6556 \n", + "8 -4.7111 \n", + "9 -0.8389 \n" + ] + } + ], + "source": [ + "data = pystreamflow.load_data('03451500')\n", + "print(data.head(10))" + ] + }, + { + "cell_type": "markdown", + "id": "weekly-shame", + "metadata": {}, + "source": [ + "As seen above, the file contains columns for the year, month, day, precipitation, evaporation, streamflow, maximum temperature, and minimum temperature. Precipitation and evaporation are measured for the river basin. The temperatures are not needed for the model that will be studied in this notebook.\n", + "\n", + "We will next extract a 200 day period of the data for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "mobile-chinese", + "metadata": {}, + "outputs": [], + "source": [ + "precip = data['precipitation'].to_numpy()[365:566]\n", + "evap = data['evaporation'].to_numpy()[365:566]\n", + "flow = data['streamflow'].to_numpy()[365:566]\n", + "all_times = np.arange(len(precip))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "monthly-crack", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(all_times, precip)\n", + "plt.xlabel('Time')\n", + "plt.ylabel('Precipitation')\n", + "plt.show()\n", + "\n", + "plt.plot(all_times, evap)\n", + "plt.xlabel('Time')\n", + "plt.ylabel('Evaporation')\n", + "plt.show()\n", + "\n", + "plt.plot(all_times, flow)\n", + "plt.xlabel('Time')\n", + "plt.ylabel('River discharge')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "inclusive-landing", + "metadata": {}, + "source": [ + "The two model inputs (precipitation and evaporation) and the model output (river discharge) are shown in the plots above. The river discharge tends to increase following rainfall. This behavior depends on the flow of water through the river basin, and it is modelled by the `pystreamflow.RiverModel` object.\n", + "\n", + "The model keeps track of the level of water stored in various compartments over time. However, the initial level of water in each compartment is unknown. These values could be treated as unknown variables and added to the inference problem, but this increases the dimensionality and makes inference more challenging. Thus, the accepted practice is to set all initial values to some low value (assuming the river basin is completely dry), and then run the simulation for some time with precipitation and evaporation available before comparing its output to discharge data. In this notebook, we will use a 100 day \"warm up\" period. Thus, the discharge data we supply to the model will begin at day 100, while the precipitation and evaporation data will start at day 0." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "cooperative-genesis", + "metadata": {}, + "outputs": [], + "source": [ + "data_times = all_times[100:200]\n", + "data_flow = flow[100:200]" + ] + }, + { + "cell_type": "markdown", + "id": "focused-knitting", + "metadata": {}, + "source": [ + "Evaluations of the RiverModel involve the integration of a system of differential equations. If these equations are not solved with sufficient accuracy, the likelihood surface will be exhibit jaggedness, and MCMC will produce a poor estimate of the parameter posterior.\n", + "\n", + "pystreamflow provides two solver options, `scipy` and `scikit` (cvode), and allows the user to select the relative tolerance and absolute tolerance for the solve. The following figure shows how too large values of rtol and atol will cause problems for inference. In this case, the default settings result in an acceptable likelihood surface." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "compound-while", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "m = pystreamflow.RiverModel(\n", + " all_times, precip, evap, solver='scipy', rtol=1e-3, atol=1e-3)\n", + "\n", + "m_accurate = pystreamflow.RiverModel(\n", + " all_times, precip, evap, solver='scikit')\n", + "\n", + "problem = pints.SingleOutputProblem(m, data_times, data_flow)\n", + "likelihood = pints.GaussianLogLikelihood(problem)\n", + "\n", + "problem_accurate = pints.SingleOutputProblem(\n", + " m_accurate, data_times, data_flow)\n", + "likelihood_accurate = pints.GaussianLogLikelihood(problem_accurate)\n", + "\n", + "params = [9.0, 800.0, 20.0, 80.0, 0.2, 70.0, 2.0, 1.0]\n", + "\n", + "q_range = np.linspace(10.0, 30.0, 400)\n", + "lls = []\n", + "lls_accurate = []\n", + "for q in q_range:\n", + " params[2] = q\n", + " lls.append(likelihood(params))\n", + " lls_accurate.append(likelihood_accurate(params))\n", + "\n", + "plt.plot(q_range, lls, label='RK23 tol=1e-3')\n", + "plt.plot(q_range, lls_accurate, label='CVODE tol=1e-7')\n", + "plt.legend()\n", + "plt.xlabel('Q_s,max')\n", + "plt.ylabel('Log likelihood')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "trying-signature", + "metadata": {}, + "source": [ + "The next step is to build the prior and likelihood used by PINTS." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "modified-carroll", + "metadata": {}, + "outputs": [], + "source": [ + "# Model\n", + "m = pystreamflow.RiverModel(all_times, precip, evap, solver='scikit')\n", + "\n", + "# Prior for each parameter\n", + "I_max_prior = pints.UniformLogPrior(0, 10)\n", + "S_umax_prior = pints.UniformLogPrior(10, 1000)\n", + "Q_smax_prior = pints.UniformLogPrior(0, 100)\n", + "alpha_e_prior = pints.UniformLogPrior(0, 100)\n", + "alpha_f_prior = pints.UniformLogPrior(-10, 10)\n", + "K_s_prior = pints.UniformLogPrior(0, 150)\n", + "K_f_prior = pints.UniformLogPrior(0, 10)\n", + "sigma_prior = pints.UniformLogPrior(0, 10)\n", + "\n", + "# Make posterior for pints\n", + "problem = pints.SingleOutputProblem(m, data_times, data_flow)\n", + "likelihood = pints.GaussianLogLikelihood(problem)\n", + "prior = pints.ComposedLogPrior(\n", + " I_max_prior,\n", + " S_umax_prior,\n", + " Q_smax_prior,\n", + " alpha_e_prior,\n", + " alpha_f_prior,\n", + " K_s_prior,\n", + " K_f_prior,\n", + " sigma_prior\n", + ")\n", + "posterior = pints.LogPosterior(likelihood, prior)" + ] + }, + { + "cell_type": "markdown", + "id": "civil-glory", + "metadata": {}, + "source": [ + "We can then use MCMC to infer the posterior distribution of the model parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "institutional-hungary", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using DiffeRential Evolution Adaptive Metropolis (DREAM) MCMC\n", + "Generating 6 chains.\n", + "Running in parallel with 6 worker processess.\n", + "Iter. Eval. Time m:s\n", + "0 6 0:00.4\n", + "1 12 0:00.7\n", + "2 18 0:00.9\n", + "3 24 0:01.2\n", + "20 126 0:06.9\n", + "40 246 0:13.0\n", + "60 366 0:19.0\n", + "80 486 0:25.2\n", + "100 606 0:31.1\n", + "120 726 0:37.0\n", + "140 846 0:42.7\n", + "160 966 0:48.0\n", + "180 1086 0:53.3\n", + "Initial phase completed.\n", + "200 1206 0:58.6\n", + "220 1326 1:04.2\n", + "240 1446 1:09.9\n", + "260 1566 1:15.2\n", + "280 1686 1:20.5\n", + "300 1806 1:26.2\n", + "320 1926 1:31.3\n", + "340 2046 1:36.7\n", + "360 2166 1:42.2\n", + "380 2286 1:47.5\n", + "400 2406 1:53.2\n", + "420 2526 1:58.7\n", + "440 2646 2:03.8\n", + "460 2766 2:08.7\n", + "480 2886 2:13.2\n", + "500 3006 2:18.3\n", + "520 3126 2:23.1\n", + "540 3246 2:28.1\n", + "560 3366 2:32.9\n", + "580 3486 2:37.7\n", + "600 3606 2:42.6\n", + "620 3726 2:47.4\n", + "640 3846 2:52.0\n", + "660 3966 2:56.8\n", + "680 4086 3:01.5\n", + "700 4206 3:05.9\n", + "720 4326 3:10.3\n", + "740 4446 3:14.8\n", + "760 4566 3:19.7\n", + "780 4686 3:24.0\n", + "800 4806 3:28.7\n", + "820 4926 3:33.2\n", + "840 5046 3:37.5\n", + "860 5166 3:42.0\n", + "880 5286 3:46.9\n", + "900 5406 3:52.0\n", + "920 5526 3:57.0\n", + "940 5646 4:02.3\n", + "960 5766 4:07.2\n", + "980 5886 4:12.2\n", + "1000 6006 4:17.1\n", + "1020 6126 4:22.2\n", + "1040 6246 4:26.8\n", + "1060 6366 4:30.8\n", + "1080 6486 4:35.2\n", + "1100 6606 4:39.9\n", + "1120 6726 4:44.1\n", + "1140 6846 4:48.7\n", + "1160 6966 4:53.0\n", + "1180 7086 4:57.4\n", + "1200 7206 5:02.1\n", + "1220 7326 5:06.4\n", + "1240 7446 5:11.1\n", + "1260 7566 5:15.5\n", + "1280 7686 5:19.9\n", + "1300 7806 5:24.5\n", + "1320 7926 5:28.6\n", + "1340 8046 5:33.3\n", + "1360 8166 5:37.6\n", + "1380 8286 5:42.0\n", + "1400 8406 5:46.7\n", + "1420 8526 5:50.9\n", + "1440 8646 5:55.2\n", + "1460 8766 5:59.3\n", + "1480 8886 6:03.6\n", + "1500 9006 6:08.1\n", + "1520 9126 6:12.6\n", + "1540 9246 6:17.3\n", + "1560 9366 6:21.9\n", + "1580 9486 6:26.3\n", + "1600 9606 6:31.5\n", + "1620 9726 6:36.4\n", + "1640 9846 6:40.8\n", + "1660 9966 6:45.6\n", + "1680 10086 6:50.1\n", + "1700 10206 6:54.3\n", + "1720 10326 6:58.7\n", + "1740 10446 7:03.0\n", + "1760 10566 7:07.2\n", + "1780 10686 7:11.5\n", + "1800 10806 7:15.8\n", + "1820 10926 7:20.1\n", + "1840 11046 7:24.5\n", + "1860 11166 7:28.7\n", + "1880 11286 7:33.0\n", + "1900 11406 7:37.6\n", + "1920 11526 7:42.0\n", + "1940 11646 7:46.7\n", + "1960 11766 7:51.2\n", + "1980 11886 7:55.5\n", + "2000 12006 8:00.1\n", + "2020 12126 8:04.8\n", + "2040 12246 8:09.3\n", + "2060 12366 8:13.8\n", + "2080 12486 8:18.5\n", + "2100 12606 8:23.1\n", + "2120 12726 8:27.7\n", + "2140 12846 8:32.6\n", + "2160 12966 8:37.6\n", + "2180 13086 8:42.3\n", + "2200 13206 8:46.4\n", + "2220 13326 8:50.7\n", + "2240 13446 8:55.1\n", + "2260 13566 8:59.2\n", + "2280 13686 9:03.4\n", + "2300 13806 9:08.1\n", + "2320 13926 9:12.5\n", + "2340 14046 9:16.9\n", + "2360 14166 9:21.6\n", + "2380 14286 9:26.1\n", + "2400 14406 9:30.6\n", + "2420 14526 9:34.9\n", + "2440 14646 9:39.1\n", + "2460 14766 9:43.4\n", + "2480 14886 9:47.8\n", + "2500 15006 9:52.3\n", + "2520 15126 9:56.9\n", + "2540 15246 10:01.5\n", + "2560 15366 10:06.0\n", + "2580 15486 10:10.6\n", + "2600 15606 10:15.4\n", + "2620 15726 10:20.1\n", + "2640 15846 10:25.2\n", + "2660 15966 10:29.9\n", + "2680 16086 10:34.5\n", + "2700 16206 10:39.9\n", + "2720 16326 10:44.5\n", + "2740 16446 10:49.0\n", + "2760 16566 10:53.7\n", + "2780 16686 10:58.5\n", + "2800 16806 11:02.9\n", + "2820 16926 11:07.3\n", + "2840 17046 11:11.7\n", + "2860 17166 11:16.5\n", + "2880 17286 11:21.1\n", + "2900 17406 11:25.2\n", + "2920 17526 11:29.7\n", + "2940 17646 11:34.0\n", + "2960 17766 11:38.3\n", + "2980 17886 11:43.4\n", + "3000 18006 11:48.8\n", + "3020 18126 11:54.3\n", + "3040 18246 11:59.3\n", + "3060 18366 12:03.6\n", + "3080 18486 12:08.2\n", + "3100 18606 12:13.1\n", + "3120 18726 12:17.7\n", + "3140 18846 12:22.3\n", + "3160 18966 12:27.1\n", + "3180 19086 12:31.4\n", + "3200 19206 12:36.2\n", + "3220 19326 12:40.6\n", + "3240 19446 12:44.7\n", + "3260 19566 12:48.9\n", + "3280 19686 12:53.3\n", + "3300 19806 12:57.6\n", + "3320 19926 13:01.8\n", + "3340 20046 13:06.0\n", + "3360 20166 13:10.2\n", + "3380 20286 13:14.6\n", + "3400 20406 13:18.8\n", + "3420 20526 13:23.0\n", + "3440 20646 13:27.1\n", + "3460 20766 13:31.3\n", + "3480 20886 13:35.6\n", + "3500 21006 13:40.1\n", + "3520 21126 13:45.1\n", + "3540 21246 13:49.9\n", + "3560 21366 13:54.3\n", + "3580 21486 13:58.9\n", + "3600 21606 14:03.8\n", + "3620 21726 14:08.5\n", + "3640 21846 14:12.8\n", + "3660 21966 14:17.1\n", + "3680 22086 14:21.5\n", + "3700 22206 14:26.1\n", + "3720 22326 14:30.6\n", + "3740 22446 14:35.1\n", + "3760 22566 14:39.8\n", + "3780 22686 14:44.5\n", + "3800 22806 14:49.1\n", + "3820 22926 14:53.7\n", + "3840 23046 14:58.2\n", + "3860 23166 15:03.0\n", + "3880 23286 15:07.6\n", + "3900 23406 15:12.4\n", + "3920 23526 15:17.3\n", + "3940 23646 15:22.0\n", + "3960 23766 15:26.4\n", + "3980 23886 15:31.1\n", + "4000 24006 15:36.2\n", + "4020 24126 15:41.0\n", + "4040 24246 15:45.7\n", + "4060 24366 15:50.3\n", + "4080 24486 15:54.7\n", + "4100 24606 15:59.0\n", + "4120 24726 16:03.2\n", + "4140 24846 16:07.7\n", + "4160 24966 16:12.3\n", + "4180 25086 16:16.5\n", + "4200 25206 16:21.0\n", + "4220 25326 16:26.0\n", + "4240 25446 16:30.5\n", + "4260 25566 16:35.1\n", + "4280 25686 16:39.5\n", + "4300 25806 16:44.2\n", + "4320 25926 16:48.5\n", + "4340 26046 16:53.1\n", + "4360 26166 16:57.7\n", + "4380 26286 17:02.2\n", + "4400 26406 17:06.7\n", + "4420 26526 17:11.2\n", + "4440 26646 17:15.9\n", + "4460 26766 17:20.2\n", + "4480 26886 17:24.7\n", + "4500 27006 17:29.1\n", + "4520 27126 17:34.3\n", + "4540 27246 17:38.8\n", + "4560 27366 17:43.3\n", + "4580 27486 17:48.2\n", + "4600 27606 17:52.7\n", + "4620 27726 17:56.9\n", + "4640 27846 18:01.5\n", + "4660 27966 18:06.0\n", + "4680 28086 18:11.3\n", + "4700 28206 18:15.7\n", + "4720 28326 18:20.3\n", + "4740 28446 18:25.0\n", + "4760 28566 18:29.6\n", + "4780 28686 18:33.9\n", + "4800 28806 18:38.3\n", + "4820 28926 18:42.5\n", + "4840 29046 18:46.9\n", + "4860 29166 18:51.3\n", + "4880 29286 18:56.3\n", + "4900 29406 19:01.0\n", + "4920 29526 19:06.0\n", + "4940 29646 19:10.5\n", + "4960 29766 19:14.8\n", + "4980 29886 19:19.4\n", + "5000 30006 19:24.0\n", + "5020 30126 19:28.1\n", + "5040 30246 19:32.6\n", + "5060 30366 19:37.5\n", + "5080 30486 19:43.3\n", + "5100 30606 19:49.0\n", + "5120 30726 19:55.0\n", + "5140 30846 20:00.8\n", + "5160 30966 20:06.6\n", + "5180 31086 20:12.3\n", + "5200 31206 20:18.3\n", + "5220 31326 20:24.1\n", + "5240 31446 20:29.8\n", + "5260 31566 20:35.5\n", + "5280 31686 20:40.9\n", + "5300 31806 20:46.6\n", + "5320 31926 20:52.4\n", + "5340 32046 20:58.0\n", + "5360 32166 21:03.6\n", + "5380 32286 21:09.2\n", + "5400 32406 21:14.6\n", + "5420 32526 21:20.5\n", + "5440 32646 21:25.1\n", + "5460 32766 21:29.4\n", + "5480 32886 21:34.1\n", + "5500 33006 21:39.7\n", + "5520 33126 21:45.4\n", + "5540 33246 21:50.9\n", + "5560 33366 21:55.3\n", + "5580 33486 21:59.5\n", + "5600 33606 22:04.4\n", + "5620 33726 22:09.9\n", + "5640 33846 22:15.4\n", + "5660 33966 22:19.9\n", + "5680 34086 22:24.6\n", + "5700 34206 22:29.0\n", + "5720 34326 22:33.6\n", + "5740 34446 22:38.0\n", + "5760 34566 22:42.7\n", + "5780 34686 22:47.4\n", + "5800 34806 22:51.8\n", + "5820 34926 22:55.9\n", + "5840 35046 23:00.8\n", + "5860 35166 23:06.6\n", + "5880 35286 23:11.7\n", + "5900 35406 23:15.9\n", + "5920 35526 23:21.2\n", + "5940 35646 23:27.1\n", + "5960 35766 23:34.8\n", + "5980 35886 23:41.9\n", + "6000 36006 23:49.3\n", + "6020 36126 23:53.9\n", + "6040 36246 23:58.6\n", + "6060 36366 24:04.1\n", + "6080 36486 24:10.0\n", + "6100 36606 24:15.7\n", + "6120 36726 24:21.9\n", + "6140 36846 24:27.8\n", + "6160 36966 24:33.8\n", + "6180 37086 24:40.3\n", + "6200 37206 24:46.7\n", + "6220 37326 24:52.5\n", + "6240 37446 24:58.3\n", + "6260 37566 25:04.2\n", + "6280 37686 25:10.2\n", + "6300 37806 25:16.5\n", + "6320 37926 25:22.5\n", + "6340 38046 25:28.2\n", + "6360 38166 25:34.0\n", + "6380 38286 25:39.9\n", + "6400 38406 25:45.4\n", + "6420 38526 25:51.1\n", + "6440 38646 25:56.7\n", + "6460 38766 26:02.4\n", + "6480 38886 26:08.2\n", + "6500 39006 26:13.9\n", + "6520 39126 26:19.7\n", + "6540 39246 26:25.4\n", + "6560 39366 26:31.1\n", + "6580 39486 26:37.3\n", + "6600 39606 26:43.1\n", + "6620 39726 26:48.9\n", + "6640 39846 26:54.5\n", + "6660 39966 27:00.4\n", + "6680 40086 27:06.5\n", + "6700 40206 27:11.7\n", + "6720 40326 27:16.6\n", + "6740 40446 27:20.9\n", + "6760 40566 27:25.7\n", + "6780 40686 27:30.2\n", + "6800 40806 27:34.8\n", + "6820 40926 27:39.4\n", + "6840 41046 27:44.2\n", + "6860 41166 27:49.0\n", + "6880 41286 27:53.4\n", + "6900 41406 27:57.9\n", + "6920 41526 28:02.6\n", + "6940 41646 28:06.9\n", + "6960 41766 28:11.2\n", + "6980 41886 28:15.4\n", + "7000 42006 28:19.9\n", + "7020 42126 28:24.2\n", + "7040 42246 28:28.9\n", + "7060 42366 28:33.3\n", + "7080 42486 28:37.6\n", + "7100 42606 28:42.7\n", + "7120 42726 28:47.5\n", + "7140 42846 28:52.1\n", + "7160 42966 28:56.7\n", + "7180 43086 29:01.5\n", + "7200 43206 29:07.1\n", + "7220 43326 29:13.1\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7240 43446 29:19.2\n", + "7260 43566 29:24.8\n", + "7280 43686 29:30.7\n", + "7300 43806 29:36.4\n", + "7320 43926 29:42.0\n", + "7340 44046 29:47.6\n", + "7360 44166 29:53.2\n", + "7380 44286 29:58.7\n", + "7400 44406 30:04.4\n", + "7420 44526 30:10.1\n", + "7440 44646 30:16.0\n", + "7460 44766 30:21.7\n", + "7480 44886 30:27.5\n", + "7500 45006 30:33.4\n", + "7520 45126 30:39.0\n", + "7540 45246 30:44.4\n", + "7560 45366 30:50.0\n", + "7580 45486 30:55.7\n", + "7600 45606 31:01.2\n", + "7620 45726 31:06.7\n", + "7640 45846 31:12.2\n", + "7660 45966 31:17.7\n", + "7680 46086 31:23.2\n", + "7700 46206 31:28.7\n", + "7720 46326 31:34.5\n", + "7740 46446 31:40.3\n", + "7760 46566 31:46.0\n", + "7780 46686 31:51.8\n", + "7800 46806 31:57.6\n", + "7820 46926 32:03.4\n", + "7840 47046 32:09.0\n", + "7860 47166 32:14.7\n", + "7880 47286 32:20.4\n", + "7900 47406 32:26.3\n", + "7920 47526 32:32.1\n", + "7940 47646 32:37.9\n", + "7960 47766 32:43.8\n", + "7980 47886 32:49.8\n", + "8000 48006 32:55.4\n", + "8020 48126 33:00.9\n", + "8040 48246 33:06.4\n", + "8060 48366 33:12.0\n", + "8080 48486 33:17.5\n", + "8100 48606 33:23.0\n", + "8120 48726 33:28.6\n", + "8140 48846 33:34.6\n", + "8160 48966 33:40.6\n", + "8180 49086 33:46.6\n", + "8200 49206 33:52.5\n", + "8220 49326 33:58.4\n", + "8240 49446 34:04.2\n", + "8260 49566 34:10.0\n", + "8280 49686 34:15.7\n", + "8300 49806 34:21.5\n", + "8320 49926 34:27.3\n", + "8340 50046 34:33.6\n", + "8360 50166 34:39.4\n", + "8380 50286 34:45.2\n", + "8400 50406 34:51.2\n", + "8420 50526 34:57.2\n", + "8440 50646 35:03.1\n", + "8460 50766 35:08.8\n", + "8480 50886 35:14.8\n", + "8500 51006 35:20.7\n", + "8520 51126 35:26.5\n", + "8540 51246 35:32.2\n", + "8560 51366 35:37.9\n", + "8580 51486 35:43.5\n", + "8600 51606 35:49.4\n", + "8620 51726 35:55.0\n", + "8640 51846 36:00.5\n", + "8660 51966 36:06.2\n", + "8680 52086 36:12.0\n", + "8700 52206 36:17.6\n", + "8720 52326 36:23.2\n", + "8740 52446 36:28.9\n", + "8760 52566 36:34.6\n", + "8780 52686 36:40.4\n", + "8800 52806 36:46.0\n", + "8820 52926 36:52.0\n", + "8840 53046 36:57.9\n", + "8860 53166 37:03.5\n", + "8880 53286 37:09.1\n", + "8900 53406 37:14.8\n", + "8920 53526 37:20.4\n", + "8940 53646 37:26.0\n", + "8960 53766 37:31.8\n", + "8980 53886 37:37.5\n", + "9000 54006 37:43.1\n", + "9020 54126 37:48.7\n", + "9040 54246 37:54.5\n", + "9060 54366 38:00.2\n", + "9080 54486 38:06.1\n", + "9100 54606 38:12.2\n", + "9120 54726 38:18.0\n", + "9140 54846 38:23.6\n", + "9160 54966 38:29.3\n", + "9180 55086 38:35.6\n", + "9200 55206 38:41.6\n", + "9220 55326 38:48.3\n", + "9240 55446 38:54.5\n", + "9260 55566 39:00.8\n", + "9280 55686 39:06.8\n", + "9300 55806 39:12.8\n", + "9320 55926 39:18.7\n", + "9340 56046 39:24.8\n", + "9360 56166 39:30.8\n", + "9380 56286 39:36.7\n", + "9400 56406 39:42.8\n", + "9420 56526 39:48.6\n", + "9440 56646 39:54.7\n", + "9460 56766 40:00.3\n", + "9480 56886 40:06.2\n", + "9500 57006 40:12.2\n", + "9520 57126 40:18.3\n", + "9540 57246 40:24.2\n", + "9560 57366 40:29.8\n", + "9580 57486 40:35.7\n", + "9600 57606 40:41.5\n", + "9620 57726 40:47.1\n", + "9640 57846 40:52.8\n", + "9660 57966 40:58.5\n", + "9680 58086 41:04.3\n", + "9700 58206 41:10.5\n", + "9720 58326 41:16.0\n", + "9740 58446 41:22.1\n", + "9760 58566 41:27.7\n", + "9780 58686 41:33.3\n", + "9800 58806 41:38.9\n", + "9820 58926 41:44.7\n", + "9840 59046 41:50.8\n", + "9860 59166 41:56.9\n", + "9880 59286 42:02.8\n", + "9900 59406 42:09.1\n", + "9920 59526 42:15.0\n", + "9940 59646 42:20.7\n", + "9960 59766 42:26.7\n", + "9980 59886 42:32.8\n", + "10000 60006 42:38.8\n", + "10020 60126 42:44.7\n", + "10040 60246 42:50.6\n", + "10060 60366 42:56.5\n", + "10080 60486 43:02.5\n", + "10100 60606 43:08.3\n", + "10120 60726 43:14.0\n", + "10140 60846 43:19.9\n", + "10160 60966 43:26.0\n", + "10180 61086 43:32.0\n", + "10200 61206 43:38.1\n", + "10220 61326 43:44.3\n", + "10240 61446 43:50.6\n", + "10260 61566 43:57.1\n", + "10280 61686 44:03.0\n", + "10300 61806 44:09.0\n", + "10320 61926 44:15.0\n", + "10340 62046 44:20.9\n", + "10360 62166 44:26.4\n", + "10380 62286 44:32.7\n", + "10400 62406 44:38.9\n", + "10420 62526 44:44.9\n", + "10440 62646 44:51.0\n", + "10460 62766 44:57.2\n", + "10480 62886 45:03.2\n", + "10500 63006 45:09.1\n", + "10520 63126 45:14.7\n", + "10540 63246 45:20.4\n", + "10560 63366 45:25.9\n", + "10580 63486 45:31.7\n", + "10600 63606 45:37.3\n", + "10620 63726 45:42.7\n", + "10640 63846 45:48.2\n", + "10660 63966 45:54.0\n", + "10680 64086 45:59.9\n", + "10700 64206 46:05.6\n", + "10720 64326 46:11.3\n", + "10740 64446 46:16.9\n", + "10760 64566 46:22.4\n", + "10780 64686 46:27.9\n", + "10800 64806 46:33.5\n", + "10820 64926 46:39.5\n", + "10840 65046 46:45.3\n", + "10860 65166 46:50.8\n", + "10880 65286 46:56.9\n", + "10900 65406 47:02.8\n", + "10920 65526 47:08.5\n", + "10940 65646 47:14.2\n", + "10960 65766 47:20.1\n", + "10980 65886 47:25.9\n", + "11000 66006 47:31.9\n", + "11020 66126 47:37.8\n", + "11040 66246 47:43.6\n", + "11060 66366 47:49.4\n", + "11080 66486 47:55.0\n", + "11100 66606 48:00.7\n", + "11120 66726 48:06.3\n", + "11140 66846 48:11.9\n", + "11160 66966 48:16.6\n", + "11180 67086 48:21.1\n", + "11200 67206 48:25.3\n", + "11220 67326 48:30.0\n", + "11240 67446 48:34.5\n", + "11260 67566 48:38.8\n", + "11280 67686 48:43.1\n", + "11300 67806 48:47.6\n", + "11320 67926 48:52.2\n", + "11340 68046 48:56.7\n", + "11360 68166 49:01.0\n", + "11380 68286 49:05.5\n", + "11400 68406 49:09.9\n", + "11420 68526 49:14.5\n", + "11440 68646 49:19.0\n", + "11460 68766 49:23.3\n", + "11480 68886 49:27.7\n", + "11500 69006 49:32.5\n", + "11520 69126 49:37.0\n", + "11540 69246 49:41.7\n", + "11560 69366 49:46.2\n", + "11580 69486 49:50.7\n", + "11600 69606 49:54.9\n", + "11620 69726 49:59.6\n", + "11640 69846 50:04.3\n", + "11660 69966 50:08.7\n", + "11680 70086 50:13.4\n", + "11700 70206 50:18.0\n", + "11720 70326 50:22.6\n", + "11740 70446 50:27.1\n", + "11760 70566 50:31.7\n", + "11780 70686 50:36.0\n", + "11800 70806 50:40.9\n", + "11820 70926 50:45.4\n", + "11840 71046 50:50.2\n", + "11860 71166 50:55.2\n", + "11880 71286 51:00.7\n", + "11900 71406 51:06.5\n", + "11920 71526 51:12.0\n", + "11940 71646 51:16.6\n", + "11960 71766 51:21.4\n", + "11980 71886 51:26.0\n", + "12000 72006 51:30.9\n", + "12020 72126 51:35.4\n", + "12040 72246 51:40.9\n", + "12060 72366 51:47.1\n", + "12080 72486 51:53.5\n", + "12100 72606 51:59.1\n", + "12120 72726 52:03.7\n", + "12140 72846 52:08.1\n", + "12160 72966 52:12.5\n", + "12180 73086 52:16.9\n", + "12200 73206 52:20.8\n", + "12220 73326 52:25.3\n", + "12240 73446 52:29.8\n", + "12260 73566 52:34.3\n", + "12280 73686 52:38.7\n", + "12300 73806 52:43.1\n", + "12320 73926 52:48.5\n", + "12340 74046 52:54.3\n", + "12360 74166 53:00.2\n", + "12380 74286 53:06.4\n", + "12400 74406 53:12.5\n", + "12420 74526 53:18.3\n", + "12440 74646 53:24.2\n", + "12460 74766 53:29.9\n", + "12480 74886 53:35.4\n", + "12500 75006 53:41.3\n", + "12520 75126 53:47.0\n", + "12540 75246 53:52.8\n", + "12560 75366 53:58.5\n", + "12580 75486 54:04.5\n", + "12600 75606 54:10.7\n", + "12620 75726 54:16.5\n", + "12640 75846 54:22.3\n", + "12660 75966 54:28.0\n", + "12680 76086 54:34.0\n", + "12700 76206 54:40.1\n", + "12720 76326 54:46.1\n", + "12740 76446 54:51.7\n", + "12760 76566 54:57.3\n", + "12780 76686 55:03.0\n", + "12800 76806 55:08.8\n", + "12820 76926 55:14.5\n", + "12840 77046 55:20.4\n", + "12860 77166 55:26.0\n", + "12880 77286 55:31.5\n", + "12900 77406 55:37.2\n", + "12920 77526 55:43.1\n", + "12940 77646 55:48.8\n", + "12960 77766 55:54.6\n", + "12980 77886 56:00.5\n", + "13000 78006 56:06.2\n", + "13020 78126 56:11.8\n", + "13040 78246 56:17.3\n", + "13060 78366 56:22.7\n", + "13080 78486 56:28.4\n", + "13100 78606 56:34.3\n", + "13120 78726 56:39.9\n", + "13140 78846 56:45.6\n", + "13160 78966 56:51.2\n", + "13180 79086 56:56.9\n", + "13200 79206 57:02.6\n", + "13220 79326 57:08.3\n", + "13240 79446 57:14.0\n", + "13260 79566 57:19.9\n", + "13280 79686 57:25.6\n", + "13300 79806 57:31.4\n", + "13320 79926 57:37.2\n", + "13340 80046 57:43.3\n", + "13360 80166 57:49.5\n", + "13380 80286 57:55.4\n", + "13400 80406 58:01.3\n", + "13420 80526 58:07.5\n", + "13440 80646 58:13.3\n", + "13460 80766 58:19.2\n", + "13480 80886 58:25.0\n", + "13500 81006 58:31.6\n", + "13520 81126 58:37.6\n", + "13540 81246 58:43.3\n", + "13560 81366 58:49.0\n", + "13580 81486 58:55.0\n", + "13600 81606 59:00.8\n", + "13620 81726 59:06.5\n", + "13640 81846 59:12.2\n", + "13660 81966 59:18.2\n", + "13680 82086 59:24.1\n", + "13700 82206 59:30.2\n", + "13720 82326 59:36.3\n", + "13740 82446 59:42.1\n", + "13760 82566 59:47.8\n", + "13780 82686 59:53.6\n", + "13800 82806 59:59.2\n", + "13820 82926 60:05.0\n", + "13840 83046 60:10.5\n", + "13860 83166 60:16.0\n", + "13880 83286 60:21.6\n", + "13900 83406 60:27.1\n", + "13920 83526 60:32.8\n", + "13940 83646 60:38.3\n", + "13960 83766 60:44.0\n", + "13980 83886 60:49.5\n", + "14000 84006 60:55.2\n", + "14020 84126 61:01.3\n", + "14040 84246 61:07.1\n", + "14060 84366 61:13.0\n", + "14080 84486 61:18.8\n", + "14100 84606 61:24.7\n", + "14120 84726 61:30.6\n", + "14140 84846 61:36.3\n", + "14160 84966 61:42.2\n", + "14180 85086 61:48.1\n", + "14200 85206 61:54.0\n", + "14220 85326 61:59.7\n", + "14240 85446 62:05.4\n", + "14260 85566 62:11.5\n", + "14280 85686 62:17.4\n", + "14300 85806 62:23.2\n", + "14320 85926 62:29.0\n", + "14340 86046 62:34.9\n", + "14360 86166 62:40.9\n", + "14380 86286 62:46.7\n", + "14400 86406 62:52.3\n", + "14420 86526 62:58.0\n", + "14440 86646 63:03.9\n", + "14460 86766 63:09.7\n", + "14480 86886 63:15.5\n", + "14500 87006 63:21.2\n", + "14520 87126 63:27.3\n", + "14540 87246 63:33.2\n", + "14560 87366 63:39.0\n", + "14580 87486 63:44.7\n", + "14600 87606 63:50.3\n", + "14620 87726 63:55.8\n", + "14640 87846 64:01.4\n", + "14660 87966 64:07.1\n", + "14680 88086 64:12.8\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14700 88206 64:18.4\n", + "14720 88326 64:24.1\n", + "14740 88446 64:29.9\n", + "14760 88566 64:35.6\n", + "14780 88686 64:41.2\n", + "14800 88806 64:46.9\n", + "14820 88926 64:52.5\n", + "14840 89046 64:58.1\n", + "14860 89166 65:03.6\n", + "14880 89286 65:09.4\n", + "14900 89406 65:15.3\n", + "14920 89526 65:21.0\n", + "14940 89646 65:26.8\n", + "14960 89766 65:32.5\n", + "14980 89886 65:38.3\n", + "15000 90006 65:44.1\n", + "15020 90126 65:49.7\n", + "15040 90246 65:55.2\n", + "15060 90366 66:01.1\n", + "15080 90486 66:07.1\n", + "15100 90606 66:12.9\n", + "15120 90726 66:18.4\n", + "15140 90846 66:24.1\n", + "15160 90966 66:29.7\n", + "15180 91086 66:35.3\n", + "15200 91206 66:41.3\n", + "15220 91326 66:47.1\n", + "15240 91446 66:53.1\n", + "15260 91566 66:58.7\n", + "15280 91686 67:04.5\n", + "15300 91806 67:10.2\n", + "15320 91926 67:15.8\n", + "15340 92046 67:21.8\n", + "15360 92166 67:27.6\n", + "15380 92286 67:33.6\n", + "15400 92406 67:39.7\n", + "15420 92526 67:45.8\n", + "15440 92646 67:51.6\n", + "15460 92766 67:57.5\n", + "15480 92886 68:03.3\n", + "15500 93006 68:08.9\n", + "15520 93126 68:14.7\n", + "15540 93246 68:20.5\n", + "15560 93366 68:26.1\n", + "15580 93486 68:31.8\n", + "15600 93606 68:37.3\n", + "15620 93726 68:43.0\n", + "15640 93846 68:48.8\n", + "15660 93966 68:54.5\n", + "15680 94086 69:00.2\n", + "15700 94206 69:05.9\n", + "15720 94326 69:11.5\n", + "15740 94446 69:17.3\n", + "15760 94566 69:22.8\n", + "15780 94686 69:28.5\n", + "15800 94806 69:34.2\n", + "15820 94926 69:39.9\n", + "15840 95046 69:45.6\n", + "15860 95166 69:51.2\n", + "15880 95286 69:56.7\n", + "15900 95406 70:02.4\n", + "15920 95526 70:08.1\n", + "15940 95646 70:13.9\n", + "15960 95766 70:19.8\n", + "15980 95886 70:25.5\n", + "16000 96006 70:31.4\n", + "16020 96126 70:37.0\n", + "16040 96246 70:42.8\n", + "16060 96366 70:48.5\n", + "16080 96486 70:54.2\n", + "16100 96606 71:00.0\n", + "16120 96726 71:05.9\n", + "16140 96846 71:11.7\n", + "16160 96966 71:17.6\n", + "16180 97086 71:23.4\n", + "16200 97206 71:29.2\n", + "16220 97326 71:34.9\n", + "16240 97446 71:40.4\n", + "16260 97566 71:46.1\n", + "16280 97686 71:51.7\n", + "16300 97806 71:57.3\n", + "16320 97926 72:03.0\n", + "16340 98046 72:08.8\n", + "16360 98166 72:14.5\n", + "16380 98286 72:20.3\n", + "16400 98406 72:26.1\n", + "16420 98526 72:32.0\n", + "16440 98646 72:37.6\n", + "16460 98766 72:43.3\n", + "16480 98886 72:49.2\n", + "16500 99006 72:55.1\n", + "16520 99126 73:00.9\n", + "16540 99246 73:06.7\n", + "16560 99366 73:12.5\n", + "16580 99486 73:18.2\n", + "16600 99606 73:24.3\n", + "16620 99726 73:29.9\n", + "16640 99846 73:35.7\n", + "16660 99966 73:41.4\n", + "16680 100086 73:47.0\n", + "16700 100206 73:52.7\n", + "16720 100326 73:58.5\n", + "16740 100446 74:04.5\n", + "16760 100566 74:10.1\n", + "16780 100686 74:15.7\n", + "16800 100806 74:21.3\n", + "16820 100926 74:26.9\n", + "16840 101046 74:32.7\n", + "16860 101166 74:38.3\n", + "16880 101286 74:43.9\n", + "16900 101406 74:49.8\n", + "16920 101526 74:55.6\n", + "16940 101646 75:01.5\n", + "16960 101766 75:07.1\n", + "16980 101886 75:12.8\n", + "17000 102006 75:18.8\n", + "17020 102126 75:24.8\n", + "17040 102246 75:30.8\n", + "17060 102366 75:36.8\n", + "17080 102486 75:42.5\n", + "17100 102606 75:48.3\n", + "17120 102726 75:54.2\n", + "17140 102846 75:59.7\n", + "17160 102966 76:05.3\n", + "17180 103086 76:10.8\n", + "17200 103206 76:16.4\n", + "17220 103326 76:22.2\n", + "17240 103446 76:28.4\n", + "17260 103566 76:34.3\n", + "17280 103686 76:40.2\n", + "17300 103806 76:46.1\n", + "17320 103926 76:52.2\n", + "17340 104046 76:58.3\n", + "17360 104166 77:04.0\n", + "17380 104286 77:09.6\n", + "17400 104406 77:15.8\n", + "17420 104526 77:21.7\n", + "17440 104646 77:27.6\n", + "17460 104766 77:33.4\n", + "17480 104886 77:39.4\n", + "17500 105006 77:45.4\n", + "17520 105126 77:51.3\n", + "17540 105246 77:57.2\n", + "17560 105366 78:02.9\n", + "17580 105486 78:08.7\n", + "17600 105606 78:14.7\n", + "17620 105726 78:21.0\n", + "17640 105846 78:26.8\n", + "17660 105966 78:32.5\n", + "17680 106086 78:38.4\n", + "17700 106206 78:44.3\n", + "17720 106326 78:50.1\n", + "17740 106446 78:55.9\n", + "17760 106566 79:01.8\n", + "17780 106686 79:07.6\n", + "17800 106806 79:13.8\n", + "17820 106926 79:19.8\n", + "17840 107046 79:25.8\n", + "17860 107166 79:31.6\n", + "17880 107286 79:37.7\n", + "17900 107406 79:43.7\n", + "17920 107526 79:49.8\n", + "17940 107646 79:55.5\n", + "17960 107766 80:01.3\n", + "17980 107886 80:07.4\n", + "18000 108006 80:13.4\n", + "18020 108126 80:19.2\n", + "18040 108246 80:25.2\n", + "18060 108366 80:31.0\n", + "18080 108486 80:36.9\n", + "18100 108606 80:42.7\n", + "18120 108726 80:48.8\n", + "18140 108846 80:54.9\n", + "18160 108966 81:00.8\n", + "18180 109086 81:06.9\n", + "18200 109206 81:12.7\n", + "18220 109326 81:19.3\n", + "18240 109446 81:25.8\n", + "18260 109566 81:31.5\n", + "18280 109686 81:37.4\n", + "18300 109806 81:43.3\n", + "18320 109926 81:49.5\n", + "18340 110046 81:55.6\n", + "18360 110166 82:01.9\n", + "18380 110286 82:07.9\n", + "18400 110406 82:14.2\n", + "18420 110526 82:21.0\n", + "18440 110646 82:26.9\n", + "18460 110766 82:32.9\n", + "18480 110886 82:38.8\n", + "18500 111006 82:44.8\n", + "18520 111126 82:50.4\n", + "18540 111246 82:56.0\n", + "18560 111366 83:01.9\n", + "18580 111486 83:07.7\n", + "18600 111606 83:13.8\n", + "18620 111726 83:19.7\n", + "18640 111846 83:25.9\n", + "18660 111966 83:31.9\n", + "18680 112086 83:37.6\n", + "18700 112206 83:43.6\n", + "18720 112326 83:49.4\n", + "18740 112446 83:55.3\n", + "18760 112566 84:01.2\n", + "18780 112686 84:07.1\n", + "18800 112806 84:12.9\n", + "18820 112926 84:19.0\n", + "18840 113046 84:24.7\n", + "18860 113166 84:30.8\n", + "18880 113286 84:36.9\n", + "18900 113406 84:42.9\n", + "18920 113526 84:48.8\n", + "18940 113646 84:54.5\n", + "18960 113766 85:00.7\n", + "18980 113886 85:06.6\n", + "19000 114006 85:12.5\n", + "19020 114126 85:18.4\n", + "19040 114246 85:24.6\n", + "19060 114366 85:31.1\n", + "19080 114486 85:37.0\n", + "19100 114606 85:42.7\n", + "19120 114726 85:48.7\n", + "19140 114846 85:54.7\n", + "19160 114966 86:00.3\n", + "19180 115086 86:06.3\n", + "19200 115206 86:12.6\n", + "19220 115326 86:18.7\n", + "19240 115446 86:24.4\n", + "19260 115566 86:30.0\n", + "19280 115686 86:35.9\n", + "19300 115806 86:41.7\n", + "19320 115926 86:47.8\n", + "19340 116046 86:53.5\n", + "19360 116166 86:59.4\n", + "19380 116286 87:05.2\n", + "19400 116406 87:11.0\n", + "19420 116526 87:17.1\n", + "19440 116646 87:22.7\n", + "19460 116766 87:28.6\n", + "19480 116886 87:34.5\n", + "19500 117006 87:40.4\n", + "19520 117126 87:46.5\n", + "19540 117246 87:52.4\n", + "19560 117366 87:58.7\n", + "19580 117486 88:04.5\n", + "19600 117606 88:10.6\n", + "19620 117726 88:17.0\n", + "19640 117846 88:23.1\n", + "19660 117966 88:29.3\n", + "19680 118086 88:35.3\n", + "19700 118206 88:41.4\n", + "19720 118326 88:47.3\n", + "19740 118446 88:53.0\n", + "19760 118566 88:58.7\n", + "19780 118686 89:04.6\n", + "19800 118806 89:10.8\n", + "19820 118926 89:16.4\n", + "19840 119046 89:22.6\n", + "19860 119166 89:28.9\n", + "19880 119286 89:35.2\n", + "19900 119406 89:41.6\n", + "19920 119526 89:47.7\n", + "19940 119646 89:54.1\n", + "19960 119766 89:59.9\n", + "19980 119886 90:05.8\n", + "20000 120006 90:11.7\n", + "20020 120126 90:17.3\n", + "20040 120246 90:23.1\n", + "20060 120366 90:29.0\n", + "20080 120486 90:34.7\n", + "20100 120606 90:40.3\n", + "20120 120726 90:46.2\n", + "20140 120846 90:52.1\n", + "20160 120966 90:58.2\n", + "20180 121086 91:04.6\n", + "20200 121206 91:10.2\n", + "20220 121326 91:15.2\n", + "20240 121446 91:19.8\n", + "20260 121566 91:24.5\n", + "20280 121686 91:29.7\n", + "20300 121806 91:34.3\n", + "20320 121926 91:38.9\n", + "20340 122046 91:44.4\n", + "20360 122166 91:49.1\n", + "20380 122286 91:54.0\n", + "20400 122406 91:58.3\n", + "20420 122526 92:03.4\n", + "20440 122646 92:08.4\n", + "20460 122766 92:13.5\n", + "20480 122886 92:18.3\n", + "20500 123006 92:23.4\n", + "20520 123126 92:28.6\n", + "20540 123246 92:33.2\n", + "20560 123366 92:38.5\n", + "20580 123486 92:43.4\n", + "20600 123606 92:48.7\n", + "20620 123726 92:53.3\n", + "20640 123846 92:58.0\n", + "20660 123966 93:02.8\n", + "20680 124086 93:07.5\n", + "20700 124206 93:12.4\n", + "20720 124326 93:17.1\n", + "20740 124446 93:21.6\n", + "20760 124566 93:25.9\n", + "20780 124686 93:30.2\n", + "20800 124806 93:34.5\n", + "20820 124926 93:38.6\n", + "20840 125046 93:42.6\n", + "20860 125166 93:46.8\n", + "20880 125286 93:51.1\n", + "20900 125406 93:55.5\n", + "20920 125526 93:59.9\n", + "20940 125646 94:04.2\n", + "20960 125766 94:08.4\n", + "20980 125886 94:12.8\n", + "21000 126006 94:17.1\n", + "21020 126126 94:21.4\n", + "21040 126246 94:25.8\n", + "21060 126366 94:30.1\n", + "21080 126486 94:34.5\n", + "21100 126606 94:39.1\n", + "21120 126726 94:44.0\n", + "21140 126846 94:48.8\n", + "21160 126966 94:53.3\n", + "21180 127086 94:57.6\n", + "21200 127206 95:02.1\n", + "21220 127326 95:06.7\n", + "21240 127446 95:11.4\n", + "21260 127566 95:16.2\n", + "21280 127686 95:20.5\n", + "21300 127806 95:24.9\n", + "21320 127926 95:29.2\n", + "21340 128046 95:33.8\n", + "21360 128166 95:39.1\n", + "21380 128286 95:43.4\n", + "21400 128406 95:47.8\n", + "21420 128526 95:52.2\n", + "21440 128646 95:56.5\n", + "21460 128766 96:00.7\n", + "21480 128886 96:05.1\n", + "21500 129006 96:09.6\n", + "21520 129126 96:14.5\n", + "21540 129246 96:18.9\n", + "21560 129366 96:23.2\n", + "21580 129486 96:27.4\n", + "21600 129606 96:32.3\n", + "21620 129726 96:36.7\n", + "21640 129846 96:41.5\n", + "21660 129966 96:46.0\n", + "21680 130086 96:50.5\n", + "21700 130206 96:54.8\n", + "21720 130326 96:59.1\n", + "21740 130446 97:03.8\n", + "21760 130566 97:08.6\n", + "21780 130686 97:13.3\n", + "21800 130806 97:17.9\n", + "21820 130926 97:22.4\n", + "21840 131046 97:27.1\n", + "21860 131166 97:31.2\n", + "21880 131286 97:35.9\n", + "21900 131406 97:40.3\n", + "21920 131526 97:45.0\n", + "21940 131646 97:49.6\n", + "21960 131766 97:54.8\n", + "21980 131886 97:59.7\n", + "22000 132006 98:04.5\n", + "22020 132126 98:09.2\n", + "22040 132246 98:13.7\n", + "22060 132366 98:18.7\n", + "22080 132486 98:23.6\n", + "22100 132606 98:28.5\n", + "22120 132726 98:33.5\n", + "22140 132846 98:38.3\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "22160 132966 98:43.3\n", + "22180 133086 98:47.6\n", + "22200 133206 98:52.3\n", + "22220 133326 98:56.5\n", + "22240 133446 99:00.8\n", + "22260 133566 99:05.4\n", + "22280 133686 99:09.9\n", + "22300 133806 99:14.3\n", + "22320 133926 99:18.8\n", + "22340 134046 99:23.0\n", + "22360 134166 99:27.0\n", + "22380 134286 99:31.3\n", + "22400 134406 99:35.6\n", + "22420 134526 99:40.2\n", + "22440 134646 99:44.6\n", + "22460 134766 99:49.2\n", + "22480 134886 99:53.5\n", + "22500 135006 99:58.0\n", + "22520 135126 100:02.5\n", + "22540 135246 100:07.2\n", + "22560 135366 100:11.5\n", + "22580 135486 100:16.1\n", + "22600 135606 100:20.3\n", + "22620 135726 100:24.8\n", + "22640 135846 100:29.9\n", + "22660 135966 100:34.4\n", + "22680 136086 100:38.9\n", + "22700 136206 100:43.4\n", + "22720 136326 100:48.1\n", + "22740 136446 100:52.9\n", + "22760 136566 100:57.0\n", + "22780 136686 101:01.4\n", + "22800 136806 101:05.4\n", + "22820 136926 101:10.3\n", + "22840 137046 101:15.0\n", + "22860 137166 101:19.6\n", + "22880 137286 101:24.1\n", + "22900 137406 101:28.9\n", + "22920 137526 101:33.4\n", + "22940 137646 101:38.0\n", + "22960 137766 101:42.6\n", + "22980 137886 101:46.9\n", + "23000 138006 101:51.7\n", + "23020 138126 101:55.9\n", + "23040 138246 102:00.7\n", + "23060 138366 102:04.9\n", + "23080 138486 102:09.2\n", + "23100 138606 102:13.4\n", + "23120 138726 102:18.2\n", + "23140 138846 102:22.3\n", + "23160 138966 102:26.5\n", + "23180 139086 102:30.6\n", + "23200 139206 102:35.0\n", + "23220 139326 102:39.3\n", + "23240 139446 102:43.6\n", + "23260 139566 102:48.1\n", + "23280 139686 102:52.8\n", + "23300 139806 102:57.3\n", + "23320 139926 103:02.1\n", + "23340 140046 103:06.6\n", + "23360 140166 103:11.3\n", + "23380 140286 103:15.9\n", + "23400 140406 103:20.4\n", + "23420 140526 103:24.8\n", + "23440 140646 103:29.1\n", + "23460 140766 103:33.5\n", + "23480 140886 103:37.8\n", + "23500 141006 103:42.2\n", + "23520 141126 103:47.4\n", + "23540 141246 103:52.1\n", + "23560 141366 103:56.6\n", + "23580 141486 104:01.0\n", + "23600 141606 104:05.2\n", + "23620 141726 104:09.6\n", + "23640 141846 104:14.3\n", + "23660 141966 104:18.5\n", + "23680 142086 104:23.0\n", + "23700 142206 104:27.2\n", + "23720 142326 104:32.1\n", + "23740 142446 104:36.4\n", + "23760 142566 104:41.1\n", + "23780 142686 104:45.9\n", + "23800 142806 104:50.5\n", + "23820 142926 104:55.1\n", + "23840 143046 104:59.7\n", + "23860 143166 105:04.2\n", + "23880 143286 105:08.6\n", + "23900 143406 105:13.3\n", + "23920 143526 105:17.9\n", + "23940 143646 105:22.7\n", + "23960 143766 105:27.2\n", + "23980 143886 105:31.9\n", + "24000 144006 105:36.5\n", + "24020 144126 105:41.0\n", + "24040 144246 105:45.2\n", + "24060 144366 105:49.6\n", + "24080 144486 105:54.2\n", + "24100 144606 105:58.7\n", + "24120 144726 106:03.1\n", + "24140 144846 106:07.6\n", + "24160 144966 106:12.0\n", + "24180 145086 106:16.2\n", + "24200 145206 106:20.3\n", + "24220 145326 106:24.7\n", + "24240 145446 106:28.8\n", + "24260 145566 106:33.1\n", + "24280 145686 106:37.5\n", + "24300 145806 106:42.3\n", + "24320 145926 106:47.2\n", + "24340 146046 106:51.6\n", + "24360 146166 106:56.0\n", + "24380 146286 107:00.5\n", + "24400 146406 107:05.1\n", + "24420 146526 107:09.7\n", + "24440 146646 107:14.1\n", + "24460 146766 107:18.5\n", + "24480 146886 107:23.1\n", + "24500 147006 107:27.5\n", + "24520 147126 107:31.8\n", + "24540 147246 107:36.2\n", + "24560 147366 107:40.6\n", + "24580 147486 107:45.3\n", + "24600 147606 107:49.8\n", + "24620 147726 107:53.8\n", + "24640 147846 107:57.9\n", + "24660 147966 108:02.5\n", + "24680 148086 108:07.1\n", + "24700 148206 108:11.5\n", + "24720 148326 108:16.2\n", + "24740 148446 108:20.8\n", + "24760 148566 108:25.3\n", + "24780 148686 108:29.6\n", + "24800 148806 108:34.4\n", + "24820 148926 108:39.1\n", + "24840 149046 108:43.5\n", + "24860 149166 108:48.1\n", + "24880 149286 108:52.8\n", + "24900 149406 108:57.0\n", + "24920 149526 109:01.6\n", + "24940 149646 109:05.6\n", + "24960 149766 109:09.9\n", + "24980 149886 109:14.4\n", + "25000 150000 109:18.6\n", + "Halting: Maximum number of iterations (25000) reached.\n" + ] + } + ], + "source": [ + "transform = pints.RectangularBoundariesTransformation([0, 10, 0, 0, -10, 0, 0, 0],\n", + " [10, 1000, 100, 100, 10, 150, 10, 10])\n", + "\n", + "num_iterations = 25000\n", + "mcmc = pints.MCMCController(\n", + "posterior, 6, prior.sample(6), method=pints.DreamMCMC, transform=transform)\n", + "mcmc.set_max_iterations(num_iterations)\n", + "mcmc.set_parallel(True)\n", + "chains = mcmc.run()" + ] + }, + { + "cell_type": "markdown", + "id": "accompanied-genius", + "metadata": {}, + "source": [ + "We can monitor the MCMC chains using `pints.plot`. Here, we plot the chains as well as the parameter posteriors and model fits." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "international-surname", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pints.plot.trace(chains)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "insured-palace", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pints.plot.pairwise(chains[0, num_iterations//2:, :], kde=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "national-review", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pints.plot.series(chains[0,num_iterations//2:,:], problem, thinning=100)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From e50b288866575e22e5ac6fb32d8027a5ed4cae2c Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 29 Mar 2021 09:22:16 +0100 Subject: [PATCH 31/44] model changes --- streamflow/README.md | 2 +- streamflow/pystreamflow/model.py | 78 +++++++----- streamflow/pystreamflow/run_inference.py | 133 -------------------- streamflow/pystreamflow/tests/test_model.py | 6 + streamflow/setup.py | 1 + 5 files changed, 53 insertions(+), 167 deletions(-) delete mode 100644 streamflow/pystreamflow/run_inference.py diff --git a/streamflow/README.md b/streamflow/README.md index 7e9dfd0..535e961 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -22,7 +22,7 @@ cmake -DLAPACK_ENABLE=ON -DSUNDIALS_INDEX_SIZE=64 ../sundials-5.1.0/ make install ``` -scikits.odes is pip installable, but it is often necessary to refer to its [installation documentation](https://scikits-odes.readthedocs.io/en/latest/installation.html), which contains troubleshooting information. +scikits.odes is pip installable, and an attempt will be made to install it when `pip install .[cvode]` is executed. However, system-specific troubleshooting is often required; see the scikit.odes [installation documentation](https://scikits-odes.readthedocs.io/en/latest/installation.html) for details. If you have conda, an alternative is to use conda forge: diff --git a/streamflow/pystreamflow/model.py b/streamflow/pystreamflow/model.py index 9d59cf6..e5d6bbf 100644 --- a/streamflow/pystreamflow/model.py +++ b/streamflow/pystreamflow/model.py @@ -21,45 +21,45 @@ class RiverModel(pints.ForwardModel): The model has four latent state variables: - S_i = interception storage - S_u = unsaturated storage - S_s = slow reservoir - S_f = fast reservoir + * S_i = interception storage + * S_u = unsaturated storage + * S_s = slow reservoir + * S_f = fast reservoir and one observed variable: - z = water flowed out of the river + * z = water flowed out of the river (In fact, it is dz/dt, or the streamflow, that is observed.) The model is characterized by the following unknown parameters: - I_max = maximum interception - S_u,max = unsaturated storage capacity - Q_s,max = maximum percolation - alpha_e = evaporation flux shape - alpha_f = runoff flux shape - K_s = slow reservoir time constant - K_f = fast reservoir time constant + * I_max = maximum interception + * S_u,max = unsaturated storage capacity + * Q_s,max = maximum percolation + * alpha_e = evaporation flux shape + * alpha_f = runoff flux shape + * K_s = slow reservoir time constant + * K_f = fast reservoir time constant as well as the following two parameters whose values are here assumed fixed and known: - alpha_s = 0 (percolation flux shape) - alpha_i = 50 (interception flux shape) + * alpha_s = 0 (percolation flux shape) + * alpha_i = 50 (interception flux shape) Appearing multiple times in the model is the flux function f, given by: - f(S, a) = (1 - exp(-a * S)) / (1 - exp(-a)) + * f(S, a) = (1 - exp(-a * S)) / (1 - exp(-a)) The behavior of all the variables is governed by a system of differential equations, namely - dS_i/dt = Precip(t) - InterceptEvap(t) - EffectPrecip(t) - dS_u/dt = EffectPrecip(t) - UnsatEvap(t) - Percolation(t) - Runoff(t) - dS_s/dt = Percolation(t) - SlowStream(t) - dS_f/dt = Runoff(t) - FastStream(t) - dz/dt = SlowStream(t) + FastStream(t) + * dS_i/dt = Precip(t) - InterceptEvap(t) - EffectPrecip(t) + * dS_u/dt = EffectPrecip(t) - UnsatEvap(t) - Percolation(t) - Runoff(t) + * dS_s/dt = Percolation(t) - SlowStream(t) + * dS_f/dt = Runoff(t) - FastStream(t) + * dz/dt = SlowStream(t) + FastStream(t) Each term is defined below. @@ -68,27 +68,34 @@ class RiverModel(pints.ForwardModel): Evap = measured or theoretical evaporation (provided as input to the model) InterceptEvap = evaporation from the interception component - InterceptEvap(t) = Evap(t) * f(S_i / I_max, alpha_i) + + * InterceptEvap(t) = Evap(t) * f(S_i / I_max, alpha_i) EffectPrecip = effective precipitation that gets sent to unsaturated storage - EffectPrecip(t) = Precip(t) * f(S_i / I_max, -alpha_i) + + * EffectPrecip(t) = Precip(t) * f(S_i / I_max, -alpha_i) UnsatEvap = evaporation from unsaturated storage - UnsatEvap(t) = max(0, Evap(t) - InterceptEvap(t)) + + * UnsatEvap(t) = max(0, Evap(t) - InterceptEvap(t)) * f(S_u / S_u,max, alpha_e) Percolation = trickling of water through the ground - Percolation(t) = Q_s,max * f(S_u / S_u,max, alpha_s) + + * Percolation(t) = Q_s,max * f(S_u / S_u,max, alpha_s) Runoff = flow of water on the surface - Runoff(t) = EffectPrecip(t) * f(S_u / S_u,max, alpha_f) + + * Runoff(t) = EffectPrecip(t) * f(S_u / S_u,max, alpha_f) SlowStream = The slow component of the river flow - SlowStream(t) = S_s / K_s + + * SlowStream(t) = S_s / K_s FastStream = The fast component of the river flow - FastStream(t) = S_f / K_f + + * FastStream(t) = S_f / K_f Models of this type are described in [1]_ and [2]_. See also the following MATLAB code @@ -174,6 +181,9 @@ def set_model_data(self, times, rainfall, evaporation): self.rainfall_data = rainfall self.evap_data = evaporation + self.rainfall_data_dict = dict(zip(times, rainfall)) + self.evap_data_dict = dict(zip(times, evaporation)) + def simulate(self, parameters, times): """Run a forward simulation. @@ -208,9 +218,8 @@ def simulate(self, parameters, times): if self.solver == 'scipy': # Define derivative function for solver def f(t, y): - index = math.floor(t - first_model_data_time) + 1 - precip = self.rainfall_data[index] - evap = self.evap_data[index] + precip = self.rainfall_data_dict.get(math.ceil(t), 0) + evap = self.evap_data_dict.get(math.ceil(t), 0) return pystreamflow.ode.ode_rhs( t, *y[:-1], @@ -238,9 +247,8 @@ def f(t, y): elif self.solver == 'scikit': # Define derivative function for solver def f(t, y, ydot): - index = math.floor(t - first_model_data_time) + 1 - precip = self.rainfall_data[index] - evap = self.evap_data[index] + precip = self.rainfall_data_dict.get(math.ceil(t), 0) + evap = self.evap_data_dict.get(math.ceil(t), 0) d = pystreamflow.ode.ode_rhs( t, *y[:-1], @@ -271,4 +279,8 @@ def f(t, y, ydot): # Take the difference, which corresponds to the measurements (flow) y = np.diff(y) + if len(y) != len(times): + # At bad parameter values, CVODE can fail and return a short y + return [np.nan] * len(times) + return y diff --git a/streamflow/pystreamflow/run_inference.py b/streamflow/pystreamflow/run_inference.py deleted file mode 100644 index a369105..0000000 --- a/streamflow/pystreamflow/run_inference.py +++ /dev/null @@ -1,133 +0,0 @@ -"""Script for running the model. -""" - -import numpy as np -import matplotlib.pyplot as plt -import pints -import pints.plot -import pystreamflow - - -def run_inference(optimize=False): - # Load data and model - data = pystreamflow.load_data('03451500') - - precip = data['precipitation'].to_numpy()[365:] - evap = data['evaporation'].to_numpy()[365:] - flow = data['streamflow'].to_numpy()[365:] - all_times = np.arange(len(precip)) - m = pystreamflow.RiverModel(all_times, precip, evap, solver='scikit') - - # Time range for data - data_times = all_times[730:1095] - data_flow = flow[730:1095] - - # Build prior - I_max_prior = pints.UniformLogPrior(0, 10) - S_umax_prior = pints.UniformLogPrior(10, 1000) - Q_smax_prior = pints.UniformLogPrior(0, 100) - alpha_e_prior = pints.UniformLogPrior(0, 100) - alpha_f_prior = pints.UniformLogPrior(-10, 10) - K_s_prior = pints.UniformLogPrior(0, 150) - K_f_prior = pints.UniformLogPrior(0, 10) - sigma_prior = pints.UniformLogPrior(0, 1e6) - - # Good parameter values - params = [9.0, 200.0, 7.0, 85.0, 0.2, 70.0, 2.5, 1.0] - - # Make objects for pints - problem = pints.SingleOutputProblem(m, data_times, data_flow) - likelihood = pints.GaussianLogLikelihood(problem) - prior = pints.ComposedLogPrior( - I_max_prior, - S_umax_prior, - Q_smax_prior, - alpha_e_prior, - alpha_f_prior, - K_s_prior, - K_f_prior, - sigma_prior - ) - posterior = pints.LogPosterior(likelihood, prior) - - if optimize: - opt = pints.OptimisationController( - posterior, params, method=pints.SNES) - opt.set_parallel(True) - opt.set_max_iterations(10) - p, _ = opt.run() - p = params - - # Plot results - y = m.simulate(p[:-1], data_times) - fig = plt.figure() - ax = fig.add_subplot(1, 1, 1) - ax.plot(data_times, y, label='Fit') - ax.plot( - data_times, data_flow, 'x-', label='Data', color='k', alpha=0.5) - ax.set_xlabel('Time (days)') - ax.legend() - plt.show() - - else: - mcmc = pints.MCMCController( - posterior, 6, [params]*6, method=pints.DreamMCMC) - mcmc.set_max_iterations(10) - mcmc.set_parallel(True) - chains = mcmc.run() - - pints.plot.trace(chains) - plt.show() - - pints.plot.pairwise(chains[0, :, :], kde=True) - plt.show() - - -def plot_likelihood(): - # Load data and model - data = pystreamflow.load_data('03451500') - - precip = data['precipitation'].to_numpy()[365:] - evap = data['evaporation'].to_numpy()[365:] - flow = data['streamflow'].to_numpy()[365:] - all_times = np.arange(len(precip)) - m = pystreamflow.RiverModel( - all_times, precip, evap, solver='scipy', rtol=1e-3, atol=1e-3) - m_accurate = pystreamflow.RiverModel( - all_times, precip, evap, solver='scikit') - - # Time range for data - data_times = all_times[730:1095] - data_flow = flow[730:1095] - - # Make objects for pints - problem = pints.SingleOutputProblem(m, data_times, data_flow) - likelihood = pints.GaussianLogLikelihood(problem) - - problem_accurate = pints.SingleOutputProblem( - m_accurate, data_times, data_flow) - likelihood_accurate = pints.GaussianLogLikelihood(problem_accurate) - - # Other parameters - params = [9.0, 200.0, 7.0, 85.0, 0.2, 70.0, 2.5, 1.0] - - # Get a slice of the likelihood - q_range = np.linspace(6.0, 10.0, 50) - lls = [] - lls_accurate = [] - for q in q_range: - params[2] = q - lls.append(likelihood(params)) - lls_accurate.append(likelihood_accurate(params)) - - plt.plot(q_range, lls, label='RK23 tol=1e-3') - plt.plot(q_range, lls_accurate, label='CVODE tol=1e-7') - plt.legend() - plt.xlabel('Q_s,max') - plt.ylabel('Log likelihood') - plt.show() - - -if __name__ == '__main__': - plot_likelihood() - run_inference(optimize=False) diff --git a/streamflow/pystreamflow/tests/test_model.py b/streamflow/pystreamflow/tests/test_model.py index 3bed31e..2ff1cde 100644 --- a/streamflow/pystreamflow/tests/test_model.py +++ b/streamflow/pystreamflow/tests/test_model.py @@ -92,6 +92,12 @@ def test_set_model_data(self): self.assertEqual(m.rainfall_data, self.precip) self.assertEqual(m.evap_data, self.evap) + self.assertEqual(m.rainfall_data_dict[1], 0) + self.assertEqual(m.evap_data_dict[1], 3) + + self.assertEqual(m.rainfall_data_dict[7], 1) + self.assertEqual(m.evap_data_dict[7], 5.5) + def test_simulate(self): # Test running simulate params = [2.5, 100, 7, 1, -0.5, 60, 3.25] diff --git a/streamflow/setup.py b/streamflow/setup.py index 90dbbff..32eb1fd 100644 --- a/streamflow/setup.py +++ b/streamflow/setup.py @@ -20,6 +20,7 @@ extras_require={ 'dev': [ 'flake8>=3', + 'sphinx', ], 'cvode': [ 'scikits.odes', From 926ff708995b3c558dd3edc9bb549dfde1c079ee Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 29 Mar 2021 09:23:59 +0100 Subject: [PATCH 32/44] model readme and docs --- docs/Makefile | 20 +++++ docs/make.bat | 36 +++++++++ docs/source/conf.py | 147 +++++++++++++++++++++++++++++++++++ docs/source/index.rst | 9 +++ docs/source/pystreamflow.rst | 22 ++++++ streamflow/README.md | 2 +- 6 files changed, 235 insertions(+), 1 deletion(-) create mode 100644 docs/Makefile create mode 100644 docs/make.bat create mode 100644 docs/source/conf.py create mode 100644 docs/source/index.rst create mode 100644 docs/source/pystreamflow.rst diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..177a8b9 --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +SPHINXPROJ = differential-equations-inference-db +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..4fa2fb9 --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,36 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=source +set BUILDDIR=build +set SPHINXPROJ=differential-equations-inference-db + +if "%1" == "" goto help + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 +) + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% + +:end +popd diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 0000000..346c9d5 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,147 @@ +# -*- coding: utf-8 -*- +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +# import os +# import sys +# sys.path.insert(0, os.path.abspath('.')) +import sphinx + +# -- General configuration ------------------------------------------------ + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'sphinx.ext.autodoc', + 'sphinx.ext.doctest', + 'sphinx.ext.mathjax', + 'sphinx.ext.napoleon', + 'sphinx.ext.viewcode', +] + +# Autodoc defaults +if int(sphinx.__version__.split('.')[1]) < 8: + autodoc_default_flags = [ + 'members', + 'inherited-members', + # 'show-inheritance', + ] +else: + autodoc_default_options = { + 'members': None, + 'inherited-members': None, + } + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# +# source_suffix = ['.rst', '.md'] +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +project = u'model' + +# The version info for the project you're documenting, acts as replacement for +# |version| and |release|, also used in various other places throughout the +# built documents. +# + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = None + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This patterns also effect to html_static_path and html_extra_path +exclude_patterns = [] + +# Suppress warnings about unused footnotes (i.e. citations of papers) +suppress_warnings = [ + 'ref.footnote', +] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'sphinx' + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = False + + +# -- Options for HTML output ---------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'alabaster' + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +# +html_theme_options = { + + # See: https://alabaster.readthedocs.io/en/latest/customization.html + + # Fixed sidebar is unusable: Doesn't have its own scrollbar! + # 'fixed_sidebar': True, + + 'page_width': '1280px', + 'sidebar_width': '320px', +} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = [] + + +# -- Options for HTMLHelp output ------------------------------------------ + +# Output file base name for HTML help builder. +htmlhelp_basename = 'modelsdoc' + + +# -- Options for LaTeX output --------------------------------------------- + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} diff --git a/docs/source/index.rst b/docs/source/index.rst new file mode 100644 index 0000000..8e1243c --- /dev/null +++ b/docs/source/index.rst @@ -0,0 +1,9 @@ +Welcome to the differential-equations-inference-db documentation +================================================================ + +Contents +======== + +.. toctree:: + + pystreamflow diff --git a/docs/source/pystreamflow.rst b/docs/source/pystreamflow.rst new file mode 100644 index 0000000..8c03f85 --- /dev/null +++ b/docs/source/pystreamflow.rst @@ -0,0 +1,22 @@ +************ +pystreamflow +************ + +The pystreamflow model can be used to study river discharge data. + +This package provides a PINTS Forward Model for simulation and inference, and a +function for loading precipitation, evaporation, and discharge data in Pandas +format. + +.. currentmodule:: pystreamflow + +Forward model +************* + +.. autoclass:: pystreamflow.RiverModel + :members: __init__, simulate, set_model_data + +Data +**** + +.. autofunction:: pystreamflow.load_data diff --git a/streamflow/README.md b/streamflow/README.md index 535e961..ee95250 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -34,4 +34,4 @@ conda install -c conda-forge scikits.odes Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). -Refer to the notebook in the examples directory for typical usage. +The [notebook](examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. From 862df6ac718127dfb2eb4e123ecf50633d3124ab Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 29 Mar 2021 09:24:29 +0100 Subject: [PATCH 33/44] actions yaml name --- .github/workflows/unit-python-ver-test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/unit-python-ver-test.yml b/.github/workflows/unit-python-ver-test.yml index d35fb25..a0d68c3 100644 --- a/.github/workflows/unit-python-ver-test.yml +++ b/.github/workflows/unit-python-ver-test.yml @@ -32,7 +32,7 @@ jobs: python-version: ${{ matrix.python-version }} architecture: x64 - - name: Install dependencies + - name: Install SUNDIALS run: | sudo apt-get -qq update; sudo apt-get install -y libopenblas-dev liblapack-dev From c972fcf676d4f2ebaf5db0dde117de3adbc32467 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 29 Mar 2021 09:28:22 +0100 Subject: [PATCH 34/44] repo readme name --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 7ab77f0..77e6574 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -# pints-models +# bayesian-differential-equations-db -The purpose of pints-models is to present Python implementations of scientific time series models from various disciplines. +The purpose of bayesian-differential-equations-db is to present Python implementations of scientific time series models from various disciplines. While the `pints.toy` module already includes a number of simple models and distributions, this repository is intended for more complex models associated with real experimental data. From ec52ee50b1603ef161cbfc4c8eeb5b0590e5cc33 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 11:44:21 +0100 Subject: [PATCH 35/44] add to readme --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 77e6574..bdcfc08 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,11 @@ # bayesian-differential-equations-db -The purpose of bayesian-differential-equations-db is to present Python implementations of scientific time series models from various disciplines. +The purpose of bayesian-differential-equations-db is to provide a database of differential equation models and associated observed time series data that represent interesting and challenging problems for inference. The database provides methods for running these models and accessing the associated observed data files using Python. -While the `pints.toy` module already includes a number of simple models and distributions, this repository is intended for more complex models associated with real experimental data. +While the [`pints.toy`](https://pints.readthedocs.io/en/latest/toy/index.html) module already includes a number of simple models and distributions, this repository is intended for more complex models associated with real experimental data. ## Models and data -[Rainfall runoff model and river discharge data for the French Broad River at Asheville, North Carolina.](streamflow/) +| Model | Reference | Features | +| ----- | --------- | -------- | +| [Rainfall-runoff river discharge data, French Broad River at Asheville, NC.](streamflow/) | [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009WR008933) | Complex noise noise process, potential model misspecification, importance of numerical accuracy | From a8c146a7d577ffd4446ea6dd7cebdedc4b7387c1 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 11:47:19 +0100 Subject: [PATCH 36/44] readme references --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index bdcfc08..659cf56 100644 --- a/README.md +++ b/README.md @@ -9,3 +9,8 @@ While the [`pints.toy`](https://pints.readthedocs.io/en/latest/toy/index.html) m | Model | Reference | Features | | ----- | --------- | -------- | | [Rainfall-runoff river discharge data, French Broad River at Asheville, NC.](streamflow/) | [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009WR008933) | Complex noise noise process, potential model misspecification, importance of numerical accuracy | + + +## References + +[1] Schoups, G., & Vrugt, J. A. (2010). A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors. _Water Resources Research_, 46(10). From ae5c0aaf97b9c58c0bbceba05669dfbf90757c7d Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 13:05:12 +0100 Subject: [PATCH 37/44] change model docstring --- README.md | 2 +- streamflow/pystreamflow/model.py | 48 +++++++++++++++++++++----------- 2 files changed, 33 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index 659cf56..bcb0d24 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ While the [`pints.toy`](https://pints.readthedocs.io/en/latest/toy/index.html) m | Model | Reference | Features | | ----- | --------- | -------- | -| [Rainfall-runoff river discharge data, French Broad River at Asheville, NC.](streamflow/) | [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009WR008933) | Complex noise noise process, potential model misspecification, importance of numerical accuracy | +| [Rainfall-runoff river discharge data, French Broad River at Asheville, NC.](streamflow/) | [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009WR008933) | Importance of numerical accuracy, complex noise process, potential model misspecification | ## References diff --git a/streamflow/pystreamflow/model.py b/streamflow/pystreamflow/model.py index e5d6bbf..af4cf3c 100644 --- a/streamflow/pystreamflow/model.py +++ b/streamflow/pystreamflow/model.py @@ -19,20 +19,45 @@ class RiverModel(pints.ForwardModel): """Rainfall runoff model of river streamflow. - The model has four latent state variables: + The model divides the movement of water through the river basin into the + following spatially-grouped components representing different hydrological + processes: + + * Interception, representing vegetation. Rainfall lands on vegetative + surfaces such as leaves and stems, at which point it may either enter + the ground or evaporate back into the air. + * Unsaturated zone, representing the soil above the water table. + + From the unsaturated zone, water can enter the river flow via one of two + processes: + + * A slow reservoir, representing percolation + * A fast reservoir, representing surface runoff + + The model has four latent state variables, each giving the level of water + in the components described above, which varies over time: * S_i = interception storage * S_u = unsaturated storage * S_s = slow reservoir * S_f = fast reservoir - and one observed variable: + and one observed variable (in fact, it is dz/dt, or the streamflow, that is + observed): * z = water flowed out of the river - (In fact, it is dz/dt, or the streamflow, that is observed.) + The behavior of all the variables is governed by a system of differential + equations, namely + + * dS_i/dt = Precip(t) - InterceptEvap(t) - EffectPrecip(t) + * dS_u/dt = EffectPrecip(t) - UnsatEvap(t) - Percolation(t) - Runoff(t) + * dS_s/dt = Percolation(t) - SlowStream(t) + * dS_f/dt = Runoff(t) - FastStream(t) + * dz/dt = SlowStream(t) + FastStream(t) - The model is characterized by the following unknown parameters: + Each term is defined below. The model is characterized by the following + unknown parameters: * I_max = maximum interception * S_u,max = unsaturated storage capacity @@ -52,17 +77,6 @@ class RiverModel(pints.ForwardModel): * f(S, a) = (1 - exp(-a * S)) / (1 - exp(-a)) - The behavior of all the variables is governed by a system of differential - equations, namely - - * dS_i/dt = Precip(t) - InterceptEvap(t) - EffectPrecip(t) - * dS_u/dt = EffectPrecip(t) - UnsatEvap(t) - Percolation(t) - Runoff(t) - * dS_s/dt = Percolation(t) - SlowStream(t) - * dS_f/dt = Runoff(t) - FastStream(t) - * dz/dt = SlowStream(t) + FastStream(t) - - Each term is defined below. - Precip = measured precipitation (provided as input to the model) Evap = measured or theoretical evaporation (provided as input to the model) @@ -97,7 +111,9 @@ class RiverModel(pints.ForwardModel): * FastStream(t) = S_f / K_f - Models of this type are described in [1]_ and [2]_. + This is the model that was studied in [1]_. See also [2]_, which contains + further details for models of this type. + See also the following MATLAB code https://github.com/Zaijab/DREAM/tree/master/examples/example_14 From d48fdf62ba542a9d642c5cca31b846d657de3983 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 23:17:21 +0100 Subject: [PATCH 38/44] move notebook --- .../data_and_inference.ipynb => examples/streamflow.ipynb | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename streamflow/examples/data_and_inference.ipynb => examples/streamflow.ipynb (100%) diff --git a/streamflow/examples/data_and_inference.ipynb b/examples/streamflow.ipynb similarity index 100% rename from streamflow/examples/data_and_inference.ipynb rename to examples/streamflow.ipynb From 1f05aed7fd2104250df45935da6f6bdf98eb1d28 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 23:18:09 +0100 Subject: [PATCH 39/44] change readme link --- streamflow/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streamflow/README.md b/streamflow/README.md index ee95250..560a95a 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -34,4 +34,4 @@ conda install -c conda-forge scikits.odes Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). -The [notebook](examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. +The [notebook](../examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. From 3359cfe20ea605f235ffaa9b9574386450072de3 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 23:19:48 +0100 Subject: [PATCH 40/44] try to fix readme link --- streamflow/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streamflow/README.md b/streamflow/README.md index 560a95a..f9673f4 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -34,4 +34,4 @@ conda install -c conda-forge scikits.odes Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). -The [notebook](../examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. +The [notebook](../../examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. From 17791716327837e91dcacc32f5ae752e082caf73 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 23:21:12 +0100 Subject: [PATCH 41/44] change file name readme --- streamflow/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streamflow/README.md b/streamflow/README.md index f9673f4..94a75b0 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -34,4 +34,4 @@ conda install -c conda-forge scikits.odes Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). -The [notebook](../../examples/data_and_inference.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. +The [notebook](../../examples/streamflow.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. From 0919a05295c0e4ffa798cd87c1c36b9bbebaa612 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Mon, 19 Apr 2021 23:23:01 +0100 Subject: [PATCH 42/44] fix link path --- streamflow/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streamflow/README.md b/streamflow/README.md index 94a75b0..07e3839 100644 --- a/streamflow/README.md +++ b/streamflow/README.md @@ -34,4 +34,4 @@ conda install -c conda-forge scikits.odes Once installed, the streamflow model can be accessed using the `pystreamflow.RiverModel` class and the data can be accessed using the `pystreamflow.load_data` function. The raw data files are available [here](pystreamflow/data/), and the model code is [here](pystreamflow/model.py). -The [notebook](../../examples/streamflow.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. +The [notebook](../examples/streamflow.ipynb) in the examples directory contains code for loading the data and running inference with MCMC. From 31628624dec61bf52da5b080ecd92a6acf421897 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Tue, 20 Apr 2021 00:50:14 +0100 Subject: [PATCH 43/44] changes to notebook --- examples/streamflow.ipynb | 77 +++++++++++++++++++++++++++++++++++++-- 1 file changed, 74 insertions(+), 3 deletions(-) diff --git a/examples/streamflow.ipynb b/examples/streamflow.ipynb index 272de77..e2981e3 100644 --- a/examples/streamflow.ipynb +++ b/examples/streamflow.ipynb @@ -161,12 +161,83 @@ }, { "cell_type": "markdown", - "id": "inclusive-landing", + "id": "tested-maker", + "metadata": {}, + "source": [ + "The two model inputs (precipitation and evaporation) and the model output (river discharge) are shown in the plots above. The river discharge tends to increase following rainfall. This behavior depends on the flow of water through the river basin, and it is modelled by the `pystreamflow.RiverModel` object." + ] + }, + { + "cell_type": "markdown", + "id": "loaded-bacon", "metadata": {}, "source": [ - "The two model inputs (precipitation and evaporation) and the model output (river discharge) are shown in the plots above. The river discharge tends to increase following rainfall. This behavior depends on the flow of water through the river basin, and it is modelled by the `pystreamflow.RiverModel` object.\n", + "This model has four latent state variables, each representing the level of water in various hydrological processes in the river basin:\n", + "\n", + "- $S_i$ (interception storage—capture of water by vegetation)\n", + "- $S_u$ (unsaturated storage—soil above the water table)\n", + "- $S_s$ (slow reservoir)\n", + "- $S_f$ (fast reservoir)\n", + "\n", + "Additionally, the observed variable is the river discharge $dz/dt$.\n", + "\n", + "The system of differential equations describing the flow of water over time is:\n", + "\n", + "- $dS_i/dt = \\text{Precip}(t) - \\text{InterceptEvap}(t) - \\text{EffectPrecip}(t)$\n", + "- $dS_u/dt = \\text{EffectPrecip}(t) - \\text{UnsatEvap}(t) - \\text{Percolation}(t) - \\text{Runoff}(t)$\n", + "- $dS_s/dt = \\text{Percolation}(t) - \\text{SlowStream}(t)$\n", + "- $dS_f/dt = \\text{Runoff}(t) - \\text{FastStream}(t)$\n", + "- $dz/dt = \\text{SlowStream}(t) + \\text{FastStream}(t)$\n", + "\n", + "Each of the named terms in the equations above is defined below in terms of the seven unknown model parameters:\n", + "\n", + "- $I_\\text{max}$ = maximum interception\n", + "- $S_\\text{u,max}$ = unsaturated storage capacity\n", + "- $Q_\\text{s,max}$ = maximum percolation\n", + "- $\\alpha_e$ = evaporation flux shape\n", + "- $\\alpha_f$ = runoff flux shape\n", + "- $K_s$ = slow reservoir time constant\n", + "- $K_f$ = fast reservoir time constant\n", "\n", - "The model keeps track of the level of water stored in various compartments over time. However, the initial level of water in each compartment is unknown. These values could be treated as unknown variables and added to the inference problem, but this increases the dimensionality and makes inference more challenging. Thus, the accepted practice is to set all initial values to some low value (assuming the river basin is completely dry), and then run the simulation for some time with precipitation and evaporation available before comparing its output to discharge data. In this notebook, we will use a 100 day \"warm up\" period. Thus, the discharge data we supply to the model will begin at day 100, while the precipitation and evaporation data will start at day 0." + "and the following two parameters which have fixed values in this version of the model:\n", + "\n", + "- $\\alpha_s$ = 0 (percolation flux shape)\n", + "- $\\alpha_i$ = 50 (interception flux shape)\n", + "\n", + "Many of the terms depend on a nonlinear flux function $f$, which is given by\n", + "\n", + "$$f(S, a) = (1 - exp(-a S)) / (1 - exp(-a))$$\n", + "\n", + "- Precip = measured precipitation (provided as input to the model)\n", + "- Evap = measured or theoretical evaporation (provided as input to the model)\n", + "- InterceptEvap = evaporation from the interception component\n", + " - $\\text{InterceptEvap}(t) = \\text{Evap}(t) * f(S_i / I_\\text{max}, \\alpha_i)$\n", + "- EffectPrecip = effective precipitation that gets sent to unsaturated\n", + " storage\n", + " - $\\text{EffectPrecip}(t) = \\text{Precip}(t) * f(S_i / I_\\text{max}, -\\alpha_i)$\n", + "- UnsatEvap = evaporation from unsaturated storage\n", + " - $\\text{UnsatEvap}(t) = \\text{max}(0, \\text{Evap}(t) - \\text{InterceptEvap}(t))\n", + " * f(S_u / S_\\text{u,max}, \\alpha_e)$\n", + "- Percolation = trickling of water through the ground\n", + " - $\\text{Percolation}(t) = Q_\\text{s,max} * f(S_u / S_\\text{u,max}, \\alpha_s)$\n", + "- Runoff = flow of water on the surface\n", + " - $\\text{Runoff}(t) = \\text{EffectPrecip}(t) * f(S_u / S_\\text{u,max}, \\alpha_f)$\n", + "- SlowStream = The slow component of the river flow\n", + " - $\\text{SlowStream}(t) = S_s / K_s$\n", + "- FastStream = The fast component of the river flow\n", + " - $\\text{FastStream}(t) = S_f / K_f$\n", + " \n", + "This model was studied in the following paper:\n", + "\n", + "Schoups, G., & Vrugt, J. A. (2010). A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors. _Water Resources Research_, 46(10)." + ] + }, + { + "cell_type": "markdown", + "id": "inclusive-landing", + "metadata": {}, + "source": [ + "The initial levels of water in $S_i, S_u, S_s, S_f$ are unknown. These values could be treated as unknown variables and added to the inference problem, but this increases the dimensionality and makes inference more challenging. Thus, the accepted practice is to set all initial values to some low value (assuming the river basin is completely dry), and then run the simulation for some time with precipitation and evaporation available before comparing its output to discharge data. In this notebook, we will use a 100 day \"warm up\" period. Thus, the discharge data we supply to the model will begin at day 100, while the precipitation and evaporation data will start at day 0." ] }, { From 60347559ed816b243ad298f7b4ae02f9d4a13548 Mon Sep 17 00:00:00 2001 From: rcw5890 Date: Tue, 20 Apr 2021 00:51:21 +0100 Subject: [PATCH 44/44] add examples to readme --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index bcb0d24..a572d5a 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,9 @@ While the [`pints.toy`](https://pints.readthedocs.io/en/latest/toy/index.html) m | ----- | --------- | -------- | | [Rainfall-runoff river discharge data, French Broad River at Asheville, NC.](streamflow/) | [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009WR008933) | Importance of numerical accuracy, complex noise process, potential model misspecification | +## Examples + +The [examples](examples/) directory contains example notebooks for each of the models. ## References