From 95de996aaf98b66f06e695302387ef26b08158c8 Mon Sep 17 00:00:00 2001 From: David A Minton Date: Thu, 8 Jul 2021 13:58:01 -0400 Subject: [PATCH] Cleaned up examples and initialized a variable in the oblateness calc to 0 --- .../1pl_1tp_encounter/init_cond.py | 5 +++-- .../1pl_1tp_encounter/param.swifter.in | 4 ++-- .../1pl_1tp_encounter/param.swiftest.in | 4 ++-- .../1pl_1tp_encounter/pl.swifter.in | 4 ++-- .../1pl_1tp_encounter/pl.swiftest.in | Bin 160 -> 160 bytes .../1pl_1tp_encounter/swiftest_vs_swifter.ipynb | 12 ++++++------ src/obl/obl.f90 | 1 + 7 files changed, 16 insertions(+), 14 deletions(-) mode change 100644 => 100755 examples/rmvs_swifter_comparison/1pl_1tp_encounter/init_cond.py diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/init_cond.py b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/init_cond.py old mode 100644 new mode 100755 index 5b5f5e76e..4c4ecb7da --- a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/init_cond.py +++ b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/init_cond.py @@ -1,3 +1,4 @@ +#!/usr/bin/env python3 """ For testing RMVS, the code generates clones of test particles based on one that is fated to impact Mercury. To use the script, modify the variables just after the "if __name__ == '__main__':" line @@ -5,7 +6,7 @@ import numpy as np from astroquery.jplhorizons import Horizons import astropy.constants as const -import swiftestio as swio +import swiftest.io as swio from scipy.io import FortranFile import sys @@ -140,7 +141,7 @@ print(f'BIN_OUT {swifter_bin}') print(f'OUT_TYPE REAL8') print(f'OUT_FORM XV') -print(f'OUT_STAT NEW') +print(f'OUT_STAT UNKNOWN') print(f'J2 {J2}') print(f'J4 {J4}') print(f'CHK_CLOSE yes') diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swifter.in b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swifter.in index 40cedba41..9174b181a 100644 --- a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swifter.in +++ b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swifter.in @@ -1,7 +1,7 @@ ! Swifter input file generated using init_cond.py T0 0 -TSTOP 0.2 -DT 0.00034223134839151266 +TSTOP 1.0 +DT 0.0006844626967830253 PL_IN pl.swifter.in TP_IN tp.swifter.in IN_TYPE ASCII diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swiftest.in b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swiftest.in index 914af3324..d43b46d64 100644 --- a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swiftest.in +++ b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/param.swiftest.in @@ -1,7 +1,7 @@ ! Swiftest input file generated using init_cond.py T0 0 -TSTOP 0.2 -DT 0.00034223134839151266 +TSTOP 1.0 +DT 0.0006844626967830253 CB_IN cb.swiftest.in PL_IN pl.swiftest.in TP_IN tp.swiftest.in diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swifter.in b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swifter.in index 6f91ef4c9..a964c7824 100644 --- a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swifter.in +++ b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swifter.in @@ -1,8 +1,8 @@ 2 ! Planet input file generated using init_cond.py -1 39.47692640889762629 +1 39.476926408897625193 0.0 0.0 0.0 0.0 0.0 0.0 -2 0.00012002693582795246295385 0.010044724833237895015 +2 0.00012002693582795244940133 0.0100447248332378922085 4.25875607065041e-05 1.0 0.0 0.0 0.0 6.283185307179586 0.0 diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swiftest.in b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/pl.swiftest.in index d3786c3df574e6b225dbd22bfec2c4995b86dd25..6f4bc1337f56833a126ada00c5685c950d805447 100644 GIT binary patch delta 35 lcmZ3$xPWm&i;R>{G~fL)d3z291_lroGM`Y$7{UhT0|1?g2Jrv@ delta 35 lcmZ3$xPWm&i;T2SG~fL)d3z291_lroGM`Y$7{UhT0|1?+2J!#^ diff --git a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/swiftest_vs_swifter.ipynb b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/swiftest_vs_swifter.ipynb index f2566d9e7..ccd070dad 100644 --- a/examples/rmvs_swifter_comparison/1pl_1tp_encounter/swiftest_vs_swifter.ipynb +++ b/examples/rmvs_swifter_comparison/1pl_1tp_encounter/swiftest_vs_swifter.ipynb @@ -23,7 +23,7 @@ "Reading Swifter file param.swifter.in\n", "Reading in time 1.355e-01\n", "Creating Dataset\n", - "Successfully converted 397 output frames.\n", + "Successfully converted 199 output frames.\n", "Swifter simulation data stored as xarray DataSet .ds\n" ] } @@ -43,9 +43,9 @@ "output_type": "stream", "text": [ "Reading Swiftest file param.swiftest.in\n", - "Reading in time 2.002e-01\n", + "Reading in time 1.001e+00\n", "Creating Dataset\n", - "Successfully converted 586 output frames.\n", + "Successfully converted 1463 output frames.\n", "Swiftest simulation data stored as xarray DataSet .ds\n" ] } @@ -81,8 +81,8 @@ { "data": { "text/plain": [ - "[,\n", - " ]" + "[,\n", + " ]" ] }, "execution_count": 6, @@ -91,7 +91,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] diff --git a/src/obl/obl.f90 b/src/obl/obl.f90 index ec34110ee..8792f2399 100644 --- a/src/obl/obl.f90 +++ b/src/obl/obl.f90 @@ -18,6 +18,7 @@ module subroutine obl_acc_body(self, system) real(DP) :: r2, irh, rinv2, t0, t1, t2, t3, fac1, fac2 associate(n => self%nbody, cb => system%cb) + self%aobl(:,:) = 0.0_DP do i = 1, n r2 = dot_product(self%xh(:, i), self%xh(:, i)) irh = 1.0_DP / sqrt(r2)