From 6b40580d0d5b508f6d80fa42da2124f613a25390 Mon Sep 17 00:00:00 2001 From: David A Minton Date: Thu, 8 Jul 2021 16:19:07 -0400 Subject: [PATCH] Refactored pte and ptb to ptbeg and ptend for consistency. Changed some of the helio interfaces for consistency --- .../swiftest_vs_swifter.ipynb | 505 +++++++++++++++++- src/helio/helio_drift.f90 | 42 +- src/helio/helio_getacch.f90 | 14 +- src/helio/helio_setup.f90 | 53 -- src/helio/helio_step.f90 | 32 +- src/modules/helio_classes.f90 | 50 +- src/modules/symba.f90 | 4 +- src/symba/symba_step_helio.f90 | 6 +- src/symba/symba_step_helio_pl.f90 | 4 +- src/symba/symba_step_interp.f90 | 14 +- src/symba/symba_step_interp_eucl.f90 | 14 +- src/whm/whm_getacch.f90 | 4 +- src/whm/whm_step.f90 | 1 - 13 files changed, 591 insertions(+), 152 deletions(-) delete mode 100644 src/helio/helio_setup.f90 diff --git a/examples/helio_swifter_comparison/swiftest_vs_swifter.ipynb b/examples/helio_swifter_comparison/swiftest_vs_swifter.ipynb index 5538aa1c6..bdc6cdd03 100644 --- a/examples/helio_swifter_comparison/swiftest_vs_swifter.ipynb +++ b/examples/helio_swifter_comparison/swiftest_vs_swifter.ipynb @@ -137,7 +137,7 @@ }, { "data": { - "image/png": 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\n", 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cj6cNGTKEPn36sGvXLuLj45k7dy7jxo1j+fLltGvXjuXLlzNu3DizyxTC77lKSzk0/H5KNmyg+fPTiRg0yOyS3GJn9k5u/upmUgpTmHHhDK+EO3i+Bf8yMBYIP9ELlFLDgGEAiYmJHi6nZhYtWnTc7d9///1J3/fkk096oBoh6iZXWRlJ94+geM0amk17ts6sxvRL8i+MXjGa8MBw5l0yj/aR3hsF5LEWvFLqciBda73uZK/TWs/SWvfSWveKjY31VDlCCB+my8tJfvAhin75haZPT6bhlVeaXZJbfPznx9z//f0kRiSy8LKFXg138GwL/lzgSqXUpUAwEKGU+q/W+t8e3KcQws9ou53kMWMo/Okn4p6cSKNrrzW7pFrTWvPahteYvWU2/Zr34/kBzxNq8/6EaB5rwWutH9Nax2utWwI3Aj/UNNx9adUpd6mLxyTE6dIOB4cffZSC5d/RZPx4Im+80eySaq3UUcqjPz/K7C2zub799bw28DVTwh38YBx8cHAwWVlZREdHe3Q4kTdprcnKyiI4ONjsUoQwjXY6OTx+PPlLv6bxI48QdestZpdUa5klmTz0w0NsydzCqJ6juKPLHabmllcCXmu9AlhRk/fGx8eTlJRERkaGW2syW3BwMPHx8WaXIYQptNPJ4XGPkf/FF8SOHEn0XXeaXVKt7crexQM/PEBuWS4vnfcSF7S4wOySfL8Fb7PZaNWqldllCCHcRDscRrh/+SWxI0cSc+89ZpdUaz8d+omxK8cSFhjGvIvn0Sm6k9klAX4Q8EKIusPocx9H/ldfETt6NDHDhppdUq1orZm/fT4vrH2BTtGdeG3gazRu0Njsso6QgBdCeIV2ODg89lHyly4ldsxoYob6d7jbXXamrJ7Cx7s/ZlCLQUzpN4WQgBCzyzqGBLwQwuO0w0HyI49Q8PU3NH54DNF33212SbWSV5bHmBVjWJO6hqHdhjLizBFYlO/Nvi4BL4TwKG23k/zIWAq++YbGjzzi9ydU9+ftZ8QPIzhceJip/aZyRZsrzC7phCTghRAeo+12kh9+hIJvv6Xx2LFE33mH2SXVyu8pvzNqxSisysqcf83hrCZnmV3SSfnedwohRJ1gXKH6sBHu4x7163DXWvP+zve5Z/k9xITE8N5l7/l8uIO04IUQHqDLy41wX77cCPfbbze7pBqzO+1MWWOcTO0f359n//ks4YEnnD/Rp0jACyHcylVWRvJDIylcsYIm4x8j6tZbzS6pxjJLMhm9YjQb0jdwd7e7GdFjBFaL1eyyqk0CXgjhNq7iYpJGjKDo19+Im/gEkUOGmF1SjW3L2sZDPzxEXlke0/tP5+JWF5td0mmTgBdCuIWzsJBD995LyfoNNH3mGRoNvtrskmps6d6lPPHrE0QGRzL/kvk+c2Xq6ZKAF0LUmjMvj4NDh1G6fbuxEtOll5pdUo04XU5e2/Aac7fO5azGZ/HieS8SHRJtdlk1JgEvhKgVR3Y2B++6m/I9e4h/5WXCLzB/kq2aKCgv4NGVj/Jz8s9c3/56HvvHY9isNrPLqhUJeCFEjdnT0zl4x53Yk5KInzGDsH/2M7ukGtmft58HfniApIIkJpwzgRs63GB2SW4hAS+EqBH74cMcuOMOHBmZJMyaRWjvf5hdUo38ePBHxq8aj81iY/a/ZtMrrpfZJbmNBLwQ4rSVHzzIgdtvx1VQSOLcOTQ480yzSzptTpeTNza+wewts+kS3YUXz3uRZmHNzC7LrSTghRCnpeyvvzh4+x1ou53Ed98hpEsXs0s6bbmluYz7eRy/HP6Fa9tdy2O9HyPIGmR2WW4nAS+EqLaSLVs4NHQY2AJInD+P4PbtzS7ptG3P2s7oFaNJL05nYp+JXNf+OrNL8hiZi0YIUS1Fq1dz8LbbsYSF0fK99/wy3JfsWcKtX9+Kw+Vg3sXz6nS4g7TghRDVUPDddySPGk1gyxYkzJmLrYnvrFpUHeXOcqb9Po0P//yQ3nG9eW7Ac0QFR5ldlsdJwAshTir3409ImTCBkG7dSHhrJtZGjcwu6bSkFqUyZsUYNmdu5o6ud/DgmQ8SYKkf0Vc/jlIIUSNZ77xL+rRphPbtS/xrr2IJDTW7pNPyR+ofPPzTw5Q6SnnxvBcZ1GKQ2SV51Sn74JVSVqXUKG8UI4TwDVpr0l9+mfRp0wi/6CLiZ77pV+Hu0i7mbJnD3cvuJiIwgkWXLap34Q7VCHittRO4ygu1CCF8gHa5SH3qKbJmvkWj66+j+YsvYAkMNLusasstzeX+7+/nlfWvcFGLi3j/8vdp3ai12WWZorpdNL8opV4HPgCKKjdqrdef6A1KqWBgJRBUsZ/FWuuJtahVCOFhurycw4+NJ/+rr4i++y5ix4xBKWV2WdW2MX0jj6x8hKySLB7v/Tg3dLjBr+p3t+oGfN+K20kVtwrQwMCTvKcMGKi1LlRK2YBVSqmvtdara1aqEMKTnIVFJD/4IEW//krsmNHEDB1qdknVprVmwfYFvLTuJZqENmHBpQvoEu1/F2C520kDXik1uuLulxiBXvW/Qn2y92qtNVBY8dBW8XPS9wghzOHIyODQPfdSumsXTadModG115hdUrXll+czYdUEfjj0AwMTBjK532QiAiPMLssnnKoFX7nwYAfgbOAzjJC/AqP75aSUUlZgHdAWeENrveY4rxkGDANITEysduFCCPco37+fg3cPxZGVRcKMNwgbMMDskqptW9Y2xqwYQ1pRGmPPHsu/O/27XnfJ/J0yGtqneJFSy4BrtdYFFY/DgY+01tVaw0op1Qj4FHhAa731RK/r1auXXrt2bXU+UgjhBiWbN3PonnsBSHhrJiHdu5tcUfVorXl/1/tM/2M60SHRPD/gec6IPcPsskyhlFqntT7uFJjV7YNPBMqrPC4HWla3AK11rlJqBXAxcMKAF0J4T+HKlSQ9NJKA6GgS58wmsGVLs0uqlvzyfCb9OollB5bxz+b/ZGq/qTQKbmR2WT6pugG/APhdKfUpRj/6YGDeyd6glIoF7BXhHgJcCEyrTbFCCPfI/eRTUiZMILhDBxJmvUVATIzZJVXLxvSNPLryUdKL0xl51kju6HoHFiVTap1ItQJeaz1FKfU18M+KTXdorTec4m1NgXkV/fAW4EOt9Zc1L1UIUVtaa7LeeouMl18htG9fmr/6KtYw37+Ayely8vbWt3lj4xvEhcbx7iXv1tsumdNR7akKKsa8n3Dc+3Fevxnwv1UAhKijtNNJ2pQp5CxcRMSVV9Ds6adRfnABU3pxOuNXjWdNyhoubnkxT/R5gvDA8FO/UchcNELUB66iIpJHj6Hwp5+MC5hGj0ZZfL9rY2XSSh5f9TilzlKe6vsUV7e9WkbJnAYJeCHqOHtaOofuu5eynbuIm/gEkUOGmF3SKZU7y3l5/css2L6A9pHtmd5/er2dbqA2JOCFqMNKd+7k0L334crPJ2Hmm4T17292Sae0P28/Y1eOZUf2Dm7qeBOje42uk8vpeYMEvBB1VOHPP5P80Egs4eG0WPgewR07ml3SSWmtWbJnCc/8/gyB1kBePf9Vzk883+yy/JoEvBB1UM77H5A6eTJBHdqT8Oab2Jo0Mbukk8opzWHSb5P4/uD3nB13NlP7TSUuNM7ssvyeBLwQdYh2uUh//gWy336bsAEDjKl+fXwe91XJq5jwywTyyvIY03MMt3a5Vca2u4kEvBB1hKukhMNjH6Vg+XIib7qJJuMfQwX47j/xEkcJL617iUU7F9G2UVtmXjiTDlEdzC6rTvHdv30hRLXZ09JJGjGC0q1bafLYOCJvvdWnhxNuz9rOuJ/HsS9vH7d0voWHznpITqR6gAS8EH6uZMtWku6/H2dhIfGvv0b4BReYXdIJOV1O3tn2Dm9seIOokChmDZpFn2Z9zC6rzpKAF8KP5S9dyuHHxhMQHU3LRQsJ7uC7XRxJBUn8Z9V/WJ++notaXsSEcybQMKih2WXVaRLwQvgh7XKR+frrZM54k5CePYl/9RUCoqPNLuu4tNZ8svsTpq+djkIxtd9ULm99uU93IXmVywW5ByCqlds/WgJeCD/jKi7m8KPjKFi+nIbXXkPTiRN9dk6Z1KJUnvz1SX45/Av/iPsHT537FM3Dmptdlm9w2mHLR7DqJSgvggc3QoB7/x4l4IXwI/bkZA7dP4KyP//06ZOpWms+/+tzpv0+DYd2ML73eP6vw//J8EcAewls+C/88irkHYQm3eBfj4HF6vZdScAL4SeK128g6YEH0OXlJLz1FmH/7Gd2SceVUZzBpN8m8VPST5zV+CyePvdpEiISzC7LfCW58MccWP0mFGdC/D/g0unQ/iLw0H/SEvBC+IHcxYtJnfQUAc2akvDmfIJa+97EW1prlu5bytQ1UylzljH27LHc3OlmabUXpMLqGfDH21BeAG0HQb9R0KKvx4K9kgS8ED7MVV5O2pSp5H7wgbFAx4svYG3UyOyy/kdmSSZPr36a7w9+T/fY7jx97tO0auj+k4Z+Jesv+PU12LgQXHboMhjOHQlNvbfurQS8ED7KnpZO8kMPUbJxI9FD7yZ25EiU1f39tLWhtebb/d8yZc0UiuxFjOo5its634bVA/3JfiNls3HidPsSsARAj5uh7wMQ3cbrpUjAC+GDitetI2nkSFxFxTR/+SUiLr7Y7JL+R2pRKlNWT2FF0gq6RHdhSr8ptGnk/RDzCVrDgV9h1Yuw5zsIDDdC/ZzhEG7epGkS8EL4EK01OYsWkTb1GWzNm5E4dy7B7dubXdYxXNrF4j8X8+K6F3G6nDzc62Fu7nQzAZZ6GCcuF+z+Fn5+EZJ+hwYxMHACnH03hDQyuzoJeCF8hausjNQnJ5H36aeEDRhAs+nPYY2IMLusY+zP28+Tvz3JurR19I7rzcQ+E+vnCBlHGWxZbPSxZ+yAholw6fNGd0xgA7OrO0ICXggfYD98mKQHH6J061Zihg8nZsT9PrVmqt1lZ962eby58U2CrEFM6juJwW0H++QYfI8qyYV178DqmVCYCo07w+BZ0PUasNrMru5/SMALYbLClSs5PPZRtN1O/Iw3CB840OySjrE9azsTf53IzuydXJh4IeN7jye2QazZZXlX7kFj/Pr6+VBeCK3Pg6tnQJuBHh/qWBsS8EKYRDudZLz2Glkz3yKoQweav/wSQa18Z2hhiaOENze9yfxt84kMjuSl817iwhYXml2Wdx3eaHTDbPvUCPKu10KfEV4d6lgbHgt4pVQCMB+IA1zALK31K57anxD+xJGRQfLDj1C8Zg0Nr72GuAkTsAQHm13WESuTVjJ1zVSSC5O5pt01jO45uv7M/Kg17F4Ov74K+382RsT0GQ6974WG8WZXd1o82YJ3AGO01uuVUuHAOqXUcq31dg/uUwifV/T77ySPGYOroJCmU6fS6JrBZpd0RGpRKs/98RzLDyyndcPWvH3R25wdd7bZZXmHo8yY/OvX1yBjJ4Q3g0GToedtEOyf/7l5LOC11ilASsX9AqXUDqA5IAEv6iXtcpE1ew4Zr7xCYGIiiXPmEtzBN4ZAOlwOFu1cxOsbXsepnTx45oPc3uV2bD544tDtirONE6dr3oLCNGPyr8GzjCtP3Ty7o7d5pQ9eKdUSOBNYc5znhgHDABITE71RjhBe58jJ4fC4cRT9tJKISy8h7qnJWMN8YzHsLRlbmLx6Mjuyd9CveT/G9x5PQng9GPqYsQvWzISNi8BRYpwwHTwTWp/v0ydOT4fHA14pFQZ8DIzUWuf//Xmt9SxgFkCvXr20p+sRwtuK164l+ZGxODIzaTLhcSJvusknhhfml+fz6vpX+XDXh8SGxPLieS9yYeKFPlGbx2gNf31vjIjZ8x1Yg6D7DUb/elxXs6tzO48GvFLKhhHu72mtP/HkvoTwNdrhIHPmW2TOmIEtPp6WCxcS0s38ENFa89W+r3j+j+fJKcvh5k43c3+P+wkLDDO7NM8pL4JN7xst9sw/IawJnP849LoDQmPMrs5jPDmKRgFzgR1a6xc9tR8hfJE9JYXkRx6hZO06Iq68grgnJvpEl8zO7J08s+YZ1qevp2t0V2ZcOIPO0Z3NLstz8pLg99mw7l0ozYWmPeCa2dD5ar/vX68OT7bgzwVuAbYopTZWbBuvtV7qwX0KYbr85ctJeXwC2O00m/YsDa+6yuySyC3N5fWNr/PRnx/RKKgRk/pO4uq2V9fNudq1hqQ/jDnYt38OaOh0hTHxV0LvOtO/Xh2eHEWzCqg/f5Ki3nOVlpI2bRq5i94nuGtXmr/wPIEtWphak9Pl5OPdH/PqhlcpLC9kSMchDO8xnIhA35rjxi0c5bDjcyPYk9dBUENj/Po/hkGj+jmAQ65kFcINynbvJnn0GMp27ybqzjtpPPIh0xfC3pC+gWfWPMOO7B2cHXc2j/3jMdpFtjO1Jo/ITzGGOa571xjmGN3WmPjrjCEQVIfPK1SDBLwQtaBdLnL++1/Sn38BS3g4CbNnm75WakZxBi+ue5Ev935JkwZNmD5gOhe1uKhujY6pnH/991mw80twOaHdIDh7KLS9EHxoojYzScALUUP2lBQOjx9P8W+rCTvvPJo+PZmAGPNGZJQ4Spi/bT5zt87F4XIwtNtQ7u52Nw1svjN9ba2VFcLmD4zFq9O3Q3AjY4jj2XdBlO+tU2s2CXghTpPWmvwvvyL1qafQTidxk5+i0XXXmdZCdmkXX+39ilfWv0JacRoXJl7I6J6j69Y87Zm7jVDfuBDK8iGuO1z5ujH5lw/Nv+5rJOCFOA3O3FxSJk2i4OtvCDnzTJpNe5ZAE6/AXpe2jul/TGdb1ja6RHdhWv9p9GzS07R63MrlhD+/MYY57v0RLDbocrVx0jT+7Ho1GqamJOCFqKbCn1eR8p//4MjOJnbUKKLvvsu0RbAP5R/ipfUvsfzAcpo0aMLUflO5rPVldWPYY2E6bPgvrH0H8g5CRHMY+DicdRuENTa7Or8iAS/EKbiKikh/4UVyFi4ksG0bWr45g5AuXUypJb88n9mbZ/PejvcIsAQwoscIbu1yKyEBIabU4zYuF+z7yRgNs/MrcDmg5T/hoinQ4VKwSlTVhPypCXESRb/9RsrjE7AfPkzUbbcSO2qUKfO2lzvL+WDXB8zaPIu8sjwGtxvMiB4j/H9lpcIM2PieMcQxZx+ERBonTXveDjF1cEinl0nAC3EczsJC0p+bTu6HHxLYogUt/ruABj2937ftdDn5at9XvLHhDQ4XHeacpucwptcYOkZ19HotbuNyGQtprHsHdnwJLju0OBfOHw+drgSb7yx84u8k4IX4m8KfV5HyxBM40tKIuvNOYh98wOutdq01K5NW8vL6l9mTu4fO0Z15su+T9GnWx6t1uFVR5tHWevZeY4jjP4YarfXYDiYXVzdJwAtRwZmfT9qz08j75BMC27Sh5aKFhJxxhtfr2Ji+kZfWvcT69PUkhicyfcB0/tXiX/55AtXlggOrjFDf8QU4yyGxDwx4FDpfBTY/P3fg4yTghQAKfviR1CefxJGVRfSwYcTcPxxLUJBXa9iTs4dXNrzCikMriAmJYcI5ExjcbjA2ix+uqpSXbIxZ3/hfyNlvLHnX606jtd64k9nV1RsS8KJes6elkzZlCgXLlhHUrh3xM2YQ0tW7I2QO5h/krc1v8eXeL2kQ0IAHz3yQmzvd7H9XoDrKYNdSY4jjnu8BbYyEOe8xaa2bRAJe1Eva6STn/ffJePEltMNB7MiRRN95h1cnCEsqSGLW5ll8/tfn2Cw2bu18K3d1vYtGwY28VoNbpG4xQn3zB1CSY4xb7/8I9LgJolqZXV29JgEv6p3SXbtIeeIJSjdtJrRvH+ImTvTqtL4phSnM2jKLJbuXYFEWhnQcwl3d7iImxI9WFirJgS2LjWBP2QjWQOh4GZx5C7Q+DyzmXAAmjiUBL+oNV3ExmTNmkPXOu1gbNqTZ9OeIuPxyr80hk1qUypwtc/h498coFNd3uJ67ut5Fk9AmXtl/rbmcsG+lEeo7vgBnGTTpBpc8B92uhwZRZlco/kYCXtQLBStWkDb5aezJyTS87lqaPPww1kaNvLLvjOIM5m6dy0e7PsKlXQxuN5ih3YbSNKypV/Zfa2nbYfP7sPkjKDhsDG/seRuc+W9o6v1RRqL6JOBFnVZ+4ABpU5+h8KefCGzdmhYL5tPg7LO9su/kwmTe2foOn+z+BJd2cVXbqxjWfRjNw5p7Zf+1UpAGWxcbC1WnbgZLgDHP+sVTof0lcjGSn5CAF3WSq7iYzFmzyJ77Nspmo/HYsUT9+2avnETdl7ePOVvmsHTvUlBwVZuruKvrXb4/fW95sTEKZtP78NcPoJ3Q7EyjC6brtRDqR+cIBCABL+oYrTUF3y4jbdo0HCkpRFx5BY3HPIytiednIdyVvYvZW2azbP8ygqxB3NjxRm7rchtxoXEe33eNVV6ItOkD2P4ZlBdARDz0Gwndb4TY9mZXKGpBAl7UGWV79pA6ZQrFv60mqGNHmk9/jga9enl8v5syNjF782x+SvqJUFsod3a9k1s630J0SLTH910jWkPaVmMUzJbFkJ8EgeHQ5Soj1FucK0ve1RES8MLvOXJyyHxjBjnvv4+lQQOaPDGByBtuQAV47tdba82q5FXM2zaPNalraBjUkOE9hnNTx5toGNTQY/utlay/jEDfuhgy/wRlhTYDYdAkY0peWRmpzpGAF37LVV5OzoL/kjlzJq6iIhrdcD2xDz5IQJTnhuuVO8tZum8p87bNY0/uHho3aMyYnmO4ocMNvnnlaV4SbP3ECPWUTYAyWui974XOV0Ooj37LEG7hsYBXSr0NXA6ka627emo/ov4x+tm/Jf35F7AnJRE6oD9NHnmEoLZtPbbP/PJ8Ptz1IQt3LCSjJIN2ke2Y0m8Kl7S8BJvVx+aKKcqEbZ/C1o/h4G/GtmZnwb+mQJfB0NAPRvEIt/BkC/5d4HVgvgf3IeqZkk2bSHt2GiUbNhDUvj0Jc+cQdu65Htvf4cLDLNi+gE92f0Kxo5g+Tfvw9LlP06dZH9MW2T6ukhzYudRoqe/9yRgBE9sRzn8cul4D0W3MrlCYwGMBr7VeqZRq6anPF/VL2b59ZL72GvlLv8YaG0Pc5KdodM01HlkTVWvNpoxNvLfjPZYfWI5CcXGri7m9y+10iPKhecuLsmDnl7Djc9i7wljmrlELOPch6HYdNDFnWUHhO6QPXvg0e2oqmW+8Qe4nn6KCgogZfh9Rd96FNSzU7fsqc5bxzb5vWLhzIduzthNuC+ffnf7Nvzv/23eGOhamG9MEbP8M9q8yWuqRLaHP/dDpKmh+FvjSNwthKtMDXik1DBgGkJiYaHI1wlc4cnLIemsWOQsXgtZE3nQTMfcMIyDG/RfbpBWl8cGuD/h498dkl2bTumFrHu/9OFe0ucI3TpzmHz4a6gd+BTREt4V+o6DzlRDXXUJdHJfpAa+1ngXMAujVq5c2uRxhMmdhEdnvvkv2O+/gKimh4VVXETvifmzN3XtiUGvNhvQNLNy5kO8OfIdLuxiQMICbO91M77je5vev5+w31ivd/hkk/W5sa9wZzhtnrFvauJOEujgl0wNeCDCCPWfRQrLffgdnTg7hgwYR+9CDbh8ZU1heyNJ9S/noz4/Ymb2T8ECjG+b/Ov4fCeEmTiWgNRzeYEwVsHMppG8ztsd1h4GPG90vclWpOE2eHCa5CDgPiFFKJQETtdZzPbU/4Z+chYXk/Pe/ZL/zLs68PEL79SP2oQcJ6dbNrfvZlrmNj/78iKX7llLiKKF9ZHsmnDOBy1tfbl43jKMM9v0Mu76CXV9DQQooCyT2NYY0drwUolqbU5uoEzw5imaIpz5b+D9nfj7ZCxaQPW8+rvx8wgYMIOb+4YR07+62fRTZi/hq71cs/nMxO7J3EBIQwsUtL+a69tfRLaabOd0wJTmwezns/MpY1q68AGyh0HYgdLgM2l8k86oLt5EuGuFVzrw8sufNJ3vBAlwFBYQNHEjM8OFuWwdVa832rO0s3r2YpXuXUuwopl1kO8b3Hs/lrS8nPDDcLfs5jYIga48R6n9+Dft/MUa+hDWBbtcaod6qv0y/KzxCAl54hf3wYbLnzSfno4/QxcWED7qQmPvuI7hzZ7d8fmZJJl/t/Yole5awJ3cPwdZgLm5ltNa7x3T3bmvdXmIMYdy9zPjJ2W9sj+1ojFHveJlxZalM6CU8TAJeeFTprj/JfnsueV8tBa2JuOxSou+6i+AOtb9gqNxZzopDK/jsr8/4JfkXnNpJ99juTDhnAhe3upiIwIjaH0B15ew3Wum7lxnL2jlKISAEWg+Avg9A20EQ6b11X4UACXjhAVpritf8Ttbbcyla+TOqQQOibr6JqFtvrfVwx8oumCV7lrB031Lyy/NpHNKY27vczpVtr6R1Qy+dlHSUGfO8VIZ65p/G9shW0PN2aDcIWvSTrhdhKgl44Tau8nIKvv6a7PkLKN22DWt0NLEjHyLyxhtrvf7pwfyDLN23lK/3fc3evL0EWYMYmDiQq9tcTe+mvbFa3D9lwTG0hrRtsPdH+OtH44IjRwlYA6FlP+h1J7T7l8z5InyKBLyoNXtaOrkfvE/OBx/izMoisHVr4p58koaDr8YSFFTjz00rSuOb/d/w9b6v2ZZljAvv2aQnT3R+gotaXuT5Lpj8lKOBvncFFKUb22Paw1m3QpvzjROkge6fNkEId5CAFzWitaZk40ZyFvyX/GXLwOkkbMAAIm/5N6F9+9b4pGZuaS7LDizj631fsy5tHRpNp6hOPNzrYS5qeZFn54QpK4QDv1QE+o+QsdPY3iAGWp9nBHrr82W6XeE3JODFaXEVFZG3dCm5H3xI6datWMLDibr5ZiJvvonAGs4llF2azYpDK1h+YDmrD6/GoR20jGjJfWfcxyWtLqFlw5ZuPYYjyovg0BpjxMv+VZC8zpiRMSAYWvSFHjcZgd6kq4x4EX5JAl6cktaa0q3byP3wQ/K/+gpXcTGBbdsQN/EJGl55JZbQ0++iSC1K5fuD3/P9we9Zl7YOl3bRPKw5t3S+hUtaXULHqI7uH9p4okC3BBjDFvs+YLTUE86Rk6OiTpCAFyfkLCgg74svyP1oMWU7dqCCg4m45BIaXX89IWf2OO0APph/kO8Ofsf3B75nc+ZmANo0bMPQbkO5sMWFdIjs4N5QLys0Juo6YaA/aJwgTegNQWHu268QPkICXhxDO50U/baavM8/o2DZcnRpKUGdOhE38QkiLr8ca3j1rwR1uBxsztjMyqSV/JT0E3ty9wDQObozD531EAMTB7p3WGNeMhxaDQfXGC311C3GVaPKasyT3veBikA/RwJd1AsS8AKtNWU7d5L32efkf/UVjowMLBERNLzqKhpddx3BXbtUu2WdV5bHquRVrExayarkVeSX5xOgAjiryVk80usRLmxxIc3CmtW+aJfTGLZ4aA0cXG3c5h0yngsIgfhexnzpiX0gUQJd1E8S8PWYPTWV/C+/JO+zzynbvRtsNsL696fhlVcSdt6Aag1xdGkXf+b8yS/Jv7AyaSUbMzbi0i6igqM4L+E8+sf3p2+zvrWfA6Y4Gw6vh6S1RqAnrTUm6gIIi4PE3nDOcOM2rjv42kLYQphAAr6esR8+TP63yyj49ltKNm4EIKRHD+ImPkH4xRcTEBl5ys9ILUrlt8O/8VvKb6xJWUN2aTYAnaI6cXe3uxkQP4Au0V1qfvGRvQRSNht95pU/OfsqnlTGWqPdbzBa5gm9oVGiLH4hxHFIwNcD5UnJFHz7LfnLvqV0k3FyM6hTJ2JHjiTikosJbHHyOVKK7EX8kfrHkVDfl2eEbXRwNH2a9aFP0z6c0/QcmoQ2Of3iXE7I2HVsmKdtM/rOASKaG/3nPW+D5j2haQ8I9uIcM0L4MQn4Oki7XJRu30HhihUU/vgjpduMq0CDu3QhdvRoIi7610lDPb88nw1pG1iXto51aevYnrUdh3YQbA2mZ5OeXNvuWs5peg7tI9uf3qgXewmkbYfUTcYJ0JTNRpg7SozngxoaYd5vlBHmzc+CcB9Z7FoIPyQBX0e4iosp+u03I9RX/IQjIwOUIqRHDxo/PIbwiy4iMOH4S9Jll2azPm09a9PWsi5tHbuyd6HR2Cw2usV0446ud9C7aW96NO5BkLWaUw8UZxshnrr5aJhn/nm0ZR7UEJp2N+ZwaXqGEehRreWCIiHcSALeT2mXi7Lduyn69TeKfv2V4jVr0OXlWMLCCO3Xj7DzBhDWvz8BUceuDuRwOfgr9y82ZWxiS+YWNmVsOtLlEmwN5ozGZ3Bfj/vo1aQX3WK6ERxwigt+7CVGF0vGTkjfDuk7jJ/KES0A4c2MMO90BcR1M+43aiH95kJ4mAS8H7EfPkzRb78Zob56Nc6sLAACW7UicsiNhJ13Hg169kQFBh55T0ZxBpszNrM5czObMzazLWsbJRVdIlHBUXSL6cZVba6iZ5OedInugu1Eo0+cdmNlovTtkF4lzHP2gXYZr7EGGhNxJfSGs+8yRrM0PQNCYzz65yKEOD4JeB+ltaZ8/35K1q+neP16iteuxX7gIADWmBhC+/YltE8fQvucg61pU7TWpBSlsDrlZ3Zk72Bn9k52ZO8gvdiYATHAEkCnqE5c0+4ausV0o3tsd+LD4o/tQ9caCtMhc7cR5lm7IXOPcT9nn3EVKBgLQ0e3NUazdLseGneCxp2NLhar/EoJ4SvkX6OPcJWXU7ZzJ8Xr11Oyzgj1yha6tWFDQs46i6ibbqJBnz6o1i3Yn7+fDbm72Zn0Hjs3G2GeX54PgEVZaBXRirPjzqZzVGfOaHwGHaM6Gv3nWhsLP+cegAN/VAT5nopQ/wvK8o4WZQ0y5jdv3NHoXmncyfiJbidztZjI7nRR5nBRandW/LiwO104nBq7y4Xd4cLh0ke2OVwu7FVvncZzdqfxOofz6PPGc5WvNR47tUZrcGmN03XsfZc2GiMurXFWvV/luWNfZxxDZbtCVTyobGYoZWyrbHioI9uOvqFym0UprBZFgEVhtViMW2vl46PbrRYIsFiqbKvyHqvCZlUEWi0EBlgJDLAYP1YLQQHGT2DVH+vR+0HWo6+3Wnyzu1EC3gS6vJyyPXso2bqV0q3bKN26ldLdu8FuB8CWkEBYv37YzuxOVvvG7I4o4a/8fezN28Bf2xZzcPVBXBXdIoGWQNpFtmNQi0F0ju5Mx6iOtAtLJKQw3QjxnP2w/kPjNvcA5Bw8NsQBGiYYQd79BqNlHtPWCPGG8eDphTT8nN3pOhKyZQ7jttTuPHK/6rYjtw4nZXbX0duKoD4a2sZzpXYXZcdsd1LqcOGsTEk3qww+m7Uy+IzQrAxSS0WoWqreVwqLxbivlML69+0WC0EBR99TNQY1Rnuj8mi01hW3lc8b/5n8z+OK1zicLpwV/4E4nBW3LlfFrT721mlsr3y93eneP8MAiyLEZiU40EqwzUKIzWo8tlkJCbQSHFBxW7E9JNBy5Plgm5WIEBtXnuGGK7z/XpfbP1EcobXGkZ5B2e7dlO3Zbdzu+pOyXbvQFWFuiYiAjm0ovvYCUhNC+bO54s+ATA7mbyGp8GtcW4wgtyoriRGJtG3Ymn/F9aGtLYI2OoBW9nJsBWmQtA+2/2Kc3CxIObaQgGDjpGZkC2MelsiWxv3IlhDVBgIbePcPxkOqhm3VwPx7yB7zuEoQVw3b0qoBXCVsjwniWoZtYICF4AALwTYrQTYLwQGV/+AthAUFEB1qIchmrdhuOfJcUNXHAcZ7A60WAiqCObAimAOsFmxWRYCl4rZiu8169HHl8wEWI4TrE5er4huPU1PucB39cRp/x2VVtzlclDuP3i9zGr8PVbeV2l2UVPyOlJQ7KbEbPzlF5Uful5Qbvzslducxvzux4UES8L7KVVqK/dAhyg8dovzAQcr376dszx7Kdu/GlZ9/5HWORmEUxkeSdmFb9jTRbIjOZ2tgBi62AFsAaJAZTGJQFB0Cwri0YTfauBRtykppUZhN4F+7ofDnoyc1KwWEQEQzYyGK1udXBHjLoyEe2tirww+1NlpOx4btiVu0RwPzBEF6JGQrtx19Tanj6Ge4K2yDbVaCAix/C9vjhGtFKAf9LWyP9xmV4V25LSjAUu8C1ddYLIogi5WgAKDmC4/VmN1Z8R9CufEfhSd4NOCVUhcDrwBWYI7W+llP7s8TtNa4CgpwpKVhT03DkZaKPS2N0uQkSvbvxZGUjErPOuY9ZSEBpDUJZH97F7sjLRyKhUOxioIGpUAKjZSNeGUjwQl9yiwklhSQWJxPgt1BlMt1zNdYgiIgrIkR3m3ON4I8ohlExB+9HxJ53CGHWmujJVLqpMxRXqVFe/T278FbVjVEHc4TvKfK/Sq3pY6jLeDa9CL8PWwrAzUo4NiwPVGIVgZx1bANDqhoDf/tdcE2K4FWCVvhfcY3KQsRwZ6bN8ljAa+UsgJvAIOAJOAPpdTnWuvtntrnyWinE1dJCfbCfErycygtyKWsIJvynAzsWRnYc7Jx5mTjzM3FlZsPBcVY84oJyi3FVv6//7vmhkJqJKQ1VqR2sJAaCamRisKGLhrY7DR1lBDndNLG4eBch5O4PAdNs5w0droICAinPLARJUExFNsSKA6LorBRFJsCosi3RpJnjSTPEkmOakSJth35GmgvcGHP1VW+LuZhd+Zgr3zeqSu+VhphW+6oXasgwKKOhGhlkAZWaYE2DLERHB5E0JGgrdKirRq2xwSx9YQtZQlbIdzLky34fwB7tNZ7AZRS7wNXAW4P+O/6d8JmB4vL+FHauLVW3AY4IdBx4vdbML6hOSyQ3wAKQyA/RFEYBYUJmtIwTXmoxhHqQjVwYg1WhGorDZxWQpw2OjiC6OwMxlUSRnFROLk6jFxCydFh7CeMXB1KLmHk6jAKaICLk3eXGGfqHdisWdisR8/eV963WRWBARbCgwOOnNW3HXleHWm9VnYnBAUc2zVQ9X5l/2/V1wZX6dMVQvgvTwZ8c6DK5YwkAb3//iKl1DBgGEBiDdf0zI8OBJcGBS6LQlsUWhm3KHBZLdgDLbhsFrQtAFdgAC5bIK7AQHRQMI4GDXA1CEcHhRJgDSNQhRNoDccWEEojWwOctlBcAaE4bWFgC8FqtRJgPc4QLYuioUURb1EVz1v+NizLOKFVObTq6PCsowFtsyr3L1UnhKiXPBnwx0up/+mZ1VrPAmYB9OrVq0Y9t9d8uqkmbxNCiDrNk9/Bk4Cqs1vFA4c9uD8hhBBVeDLg/wDaKaVaKaUCgRuBzz24PyGEEFV4rItGa+1QSo0AvsUYJvm21nqbp/YnhBDiWB4dB6+1Xgos9eQ+hBBCHJ+MgxNCiDpKAl4IIeooCXghhKijJOCFEKKOUpVzMPsCpVQGcKCGb48BMt1Yjj+QY6776tvxghzz6WqhtY493hM+FfC1oZRaq7XuZXYd3iTHXPfVt+MFOWZ3ki4aIYSooyTghRCijqpLAT/L7AJMIMdc99W34wU5ZrepM33wQgghjlWXWvBCCCGqkIAXQog6yq8CXil1sVJql1Jqj1Jq3HGeV0qpVyue36yUOsuMOt2pGsd8c8WxblZK/aqUOsOMOt3pVMdc5XVnK6WcSqnrvFmfJ1TnmJVS5ymlNiqltimlfvJ2je5Wjd/thkqpL5RSmyqO+Q4z6nQXpdTbSql0pdTWEzzv/vzSWvvFD8aUw38BrYFAYBPQ+W+vuRT4GmM1qXOANWbX7YVj7gtEVty/pD4cc5XX/YAxW+l1Ztfthb/nRhjrGSdWPG5sdt1eOObxwLSK+7FANhBodu21OOb+wFnA1hM87/b88qcW/JFFvLXW5UDlIt5VXQXM14bVQCOlVFNvF+pGpzxmrfWvWuucioerMVbO8mfV+XsGeAD4GEj3ZnEeUp1jvgn4RGt9EEBr7e/HXZ1j1kC4MhYpDsMIeId3y3QfrfVKjGM4Ebfnlz8F/PEW8W5eg9f4k9M9nrswWgD+7JTHrJRqDgwGZnqxLk+qzt9zeyBSKbVCKbVOKXWr16rzjOoc8+tAJ4ylPrcAD2mtXd4pzxRuzy+PLvjhZtVZxLtaC337kWofj1LqfIyA7+fRijyvOsf8MvCo1tppNO78XnWOOQDoCVwAhAC/KaVWa63/9HRxHlKdY74I2AgMBNoAy5VSP2ut8z1cm1ncnl/+FPDVWcS7ri30Xa3jUUp1B+YAl2its7xUm6dU55h7Ae9XhHsMcKlSyqG1XuKVCt2vur/bmVrrIqBIKbUSOAPw14CvzjHfATyrjQ7qPUqpfUBH4HfvlOh1bs8vf+qiqc4i3p8Dt1acjT4HyNNap3i7UDc65TErpRKBT4Bb/Lg1V9Upj1lr3Upr3VJr3RJYDAz343CH6v1ufwb8UykVoJRqAPQGdni5TneqzjEfxPjGglKqCdAB2OvVKr3L7fnlNy14fYJFvJVS91Y8PxNjRMWlwB6gGKMF4LeqecxPANHAjIoWrUP78Ux81TzmOqU6x6y13qGU+gbYDLiAOVrr4w638wfV/HueDLyrlNqC0X3xqNbab6cRVkotAs4DYpRSScBEwAaeyy+ZqkAIIeoof+qiEUIIcRok4IUQoo6SgBdCiDpKAl4IIeooCXghhKijJOBFnaSUaqSUGl7lcTOl1GIP7etqpdQTp3jN80qpgZ7YvxAnIsMkRZ2klGoJfKm17uqFff0KXHmyMdpKqRbAbK31vzxdjxCVpAUv6qpngTYV86dPV0q1rJyHWyl1u1JqScVc4/uUUiOUUqOVUhuUUquVUlEVr2ujlPqmYnKvn5VSHf++E6VUe6BMa52plAqv+DxbxXMRSqn9Simb1voAEK2UivPin4Go5yTgRV01DvhLa91Da/3IcZ7vijEF7z+AKUCx1vpM4DegcqbGWcADWuuewMPAjON8zrnAegCtdQGwAris4rkbgY+11vaKx+srXi+EV/jNVAVCuNmPFYFcoJTKA76o2L4F6K6UCsNYTOWjKjNWBh3nc5oCGVUezwHGAkswLjUfWuW5dKCZuw5AiFORgBf1VVmV+64qj10Y/y4sQK7WuscpPqcEaFj5QGv9S0V30ADA+rf5YoIrXi+EV0gXjairCoDwmr65Ys7xfUqp6+HIepnHW+92B9D2b9vmA4uAd/62vT3gtxOECf8jAS/qpIp58X9RSm1VSk2v4cfcDNyllNoEbOP4SweuBM5Ux6488h4QiRHyAFSceG0LrK1hLUKcNhkmKUQtKaVeAb7QWn9X8fg64Cqt9S1VXjMYOEtrPcGkMkU9JH3wQtTeVIwFOFBKvQZcgjGvd1UBwAterkvUc9KCF0KIOkr64IUQoo6SgBdCiDpKAl4IIeooCXghhKijJOCFEKKO+n84kyOxbw1iOgAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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" ] @@ -213,6 +213,507 @@ "print()" ] }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "    Radius    (time (y), id) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
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+       "    dv        (time (y), id) float64 0.0 0.0 0.0 0.0 ... 4.632 8.449 11.73
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Loop counter real(DP) :: rmag, vmag2, energy integer(I4B), dimension(:),allocatable :: iflag !! Vectorized error code flag - real(DP), dimension(:), allocatable :: dtp, mu + real(DP), dimension(:), allocatable :: dtp, mu associate(pl => self, npl => self%nbody, cb => system%cb) if (npl == 0) return @@ -58,7 +58,7 @@ module subroutine helio_drift_pl(self, system, param, dt) return end subroutine helio_drift_pl - module subroutine helio_drift_linear_pl(self, system, dt, pt) + module subroutine helio_drift_linear_pl(self, cb, dt, lbeg) !! author: David A. Minton !! !! Perform linear drift of massive bodies due to barycentric momentum of Sun @@ -67,12 +67,19 @@ module subroutine helio_drift_linear_pl(self, system, dt, pt) !! Adapted from Hal Levison's Swift routine helio_lindrift.f implicit none ! Arguments - class(helio_pl), intent(inout) :: self !! Helio massive body object - class(helio_nbody_system), intent(in) :: system !! Swiftest nbody system object - real(DP), intent(in) :: dt !! Stepsize - real(DP), dimension(:), intent(out) :: pt !! negative barycentric velocity of the central body - - associate(pl => self, npl => self%nbody, cb => system%cb) + class(helio_pl), intent(inout) :: self !! Helio massive body object + class(helio_cb), intent(in) :: cb !! Helio central bod + real(DP), intent(in) :: dt !! Stepsize + logical, intent(in) :: lbeg !! Argument that determines whether or not this is the beginning or end of the step + ! Internals + real(DP), dimension(NDIM) :: pt !! negative barycentric velocity of the central body + + associate(pl => self, npl => self%nbody) + if (lbeg) then + pt(:) = cb%ptbeg + else + pt(:) = cb%ptend + end if pt(1) = sum(pl%Gmass(1:npl) * pl%vb(1,1:npl)) pt(2) = sum(pl%Gmass(1:npl) * pl%vb(2,1:npl)) pt(3) = sum(pl%Gmass(1:npl) * pl%vb(3,1:npl)) @@ -136,7 +143,7 @@ module subroutine helio_drift_tp(self, system, param, dt) return end subroutine helio_drift_tp - module subroutine helio_drift_linear_tp(self, system, dt, pt) + module subroutine helio_drift_linear_tp(self, cb, dt, lbeg) !! author: David A. Minton !! !! Perform linear drift of test particles due to barycentric momentum of Sun @@ -146,12 +153,19 @@ module subroutine helio_drift_linear_tp(self, system, dt, pt) !! Adapted from Hal Levison's Swift routine helio_lindrift_tp.f implicit none ! Arguments - class(helio_tp), intent(inout) :: self !! Helio test particleb object - class(helio_nbody_system), intent(in) :: system !! Swiftest nbody system object - real(DP), intent(in) :: dt !! Stepsize - real(DP), dimension(:), intent(in) :: pt !! negative barycentric velocity of the central body - + class(helio_tp), intent(inout) :: self !! Helio test particleb object + class(helio_cb), intent(in) :: cb !! Helio central body + real(DP), intent(in) :: dt !! Stepsize + logical, intent(in) :: lbeg !! Argument that determines whether or not this is the beginning or end of the step + ! Internals + real(DP), dimension(NDIM) :: pt !! negative barycentric velocity of the central body + associate(tp => self, ntp => self%nbody) + if (lbeg) then + pt(:) = cb%ptbeg + else + pt(:) = cb%ptend + end if where (tp%status(1:ntp) == ACTIVE) tp%xh(1, 1:ntp) = tp%xh(1, 1:ntp) + pt(1) * dt tp%xh(2, 1:ntp) = tp%xh(2, 1:ntp) + pt(2) * dt diff --git a/src/helio/helio_getacch.f90 b/src/helio/helio_getacch.f90 index 21ae7aafe..4b598f204 100644 --- a/src/helio/helio_getacch.f90 +++ b/src/helio/helio_getacch.f90 @@ -18,7 +18,11 @@ module subroutine helio_getacch_pl(self, system, param, t, lbeg) associate(cb => system%cb, pl => self, npl => self%nbody) call helio_getacch_int_pl(pl, t) - if (param%loblatecb) call pl%accel_obl(system) + if (param%loblatecb) then + cb%aoblbeg = cb%aobl + call pl%accel_obl(system) + cb%aoblend = cb%aobl + end if if (param%lextra_force) call pl%accel_user(system, param, t) !if (param%lgr) call pl%gr_accel(param) end associate @@ -99,8 +103,8 @@ subroutine helio_getacch_int_tp(tp, system, param, t) !! Adapted from Hal Levison's Swift routine getacch_ah3_tp.f implicit none ! Arguments - class(helio_tp), intent(inout) :: tp !! WHM test particle data structure - class(swiftest_nbody_system), intent(inout) :: system !! WHM nbody system object + class(helio_tp), intent(inout) :: tp !! Helio test particle object + class(swiftest_nbody_system), intent(inout) :: system !! Swiftest nbody system object class(swiftest_parameters), intent(in) :: param !! Current run configuration parameters of real(DP), intent(in) :: t !! Current times ! Internals @@ -109,8 +113,8 @@ subroutine helio_getacch_int_tp(tp, system, param, t) real(DP), dimension(NDIM) :: dx real(DP), dimension(:, :), allocatable :: xhp - associate(ntp => tp%nbody, pl => system%pl, npl => system%pl%nbody) - if (system%lbeg) then + associate(ntp => tp%nbody, pl => system%pl, npl => system%pl%nbody, lbeg => system%lbeg) + if (lbeg) then allocate(xhp, source=pl%xbeg) else allocate(xhp, source=pl%xend) diff --git a/src/helio/helio_setup.f90 b/src/helio/helio_setup.f90 deleted file mode 100644 index b97287314..000000000 --- a/src/helio/helio_setup.f90 +++ /dev/null @@ -1,53 +0,0 @@ -submodule(helio_classes) s_helio_setup - use swiftest -contains - module subroutine helio_setup_system(self, param) - !! author: David A. Minton - !! - !! Initialize a Helio nbody system from files - implicit none - ! Arguments - class(helio_nbody_system), intent(inout) :: self !! Helio system object - class(swiftest_parameters), intent(inout) :: param !! Current run configuration parameters - - call io_read_initialize_system(self, param) - ! Make sure that the discard list gets allocated initially - call self%tp_discards%setup(self%tp%nbody) - end subroutine helio_setup_system - - module procedure helio_setup_pl - !! author: David A. Minton & Carlisle A. Wishard - !! - !! Allocate Helio planet structure - !! - !! Equivalent in functionality to David E. Kaufmann's Swifter routine helio_setup.f90 - implicit none - - !> Call allocation method for great-grandparent class (we don't need Jacobi variables from WHM/RMVS) - call setup_pl(self, n) - if (n <= 0) return - - allocate(self%ah(NDIM, n)) - self%ah(:,:) = 0.0_DP - return - end procedure helio_setup_pl - - module procedure helio_setup_tp - !! author: David A. Minton & Carlisle A. Wishard - !! - !! Allocate Helio test particle structure - !! - !! Equivalent in functionality to David E. Kaufmann's Swifter routine helio_setup.f90 - implicit none - - !> Call allocation method for great-grandparent class - call setup_tp(self, n) - if (n <= 0) return - - allocate(self%ah(NDIM, n)) - self%ah(:,:) = 0.0_DP - - return - end procedure helio_setup_tp - -end submodule s_helio_setup \ No newline at end of file diff --git a/src/helio/helio_step.f90 b/src/helio/helio_step.f90 index 1c4367228..8557477f7 100644 --- a/src/helio/helio_step.f90 +++ b/src/helio/helio_step.f90 @@ -43,15 +43,15 @@ module subroutine helio_step_pl(self, system, param, t, dt) real(DP) :: dth, msys if (self%nbody == 0) return - select type(system) - class is (helio_nbody_system) - associate(pl => self, cb => system%cb, ptb => system%ptb, pte => system%pte) + associate(pl => self) + select type(cb => system%cb) + class is (helio_cb) dth = 0.5_DP * dt if (pl%lfirst) then call pl%vh2vb(cb) pl%lfirst = .false. end if - call pl%lindrift(system, dth, ptb) + call pl%lindrift(cb, dth, lbeg=.true.) call pl%accel(system, param, t) call pl%kick(dth) call pl%set_beg_end(xbeg = pl%xh) @@ -59,10 +59,10 @@ module subroutine helio_step_pl(self, system, param, t, dt) call pl%set_beg_end(xend = pl%xh) call pl%accel(system, param, t + dt) call pl%kick(dth) - call pl%lindrift(system, dth, pte) + call pl%lindrift(cb, dth, lbeg=.false.) call pl%vb2vh(cb) - end associate - end select + end select + end associate return @@ -88,24 +88,24 @@ module subroutine helio_step_tp(self, system, param, t, dt) if (self%nbody == 0) return - select type(system) - class is (helio_nbody_system) - associate(tp => self, cb => system%cb, pl => system%pl, ptb => system%ptb, pte => system%pte) + associate(tp => self) + select type(cb => system%cb) + class is (helio_cb) dth = 0.5_DP * dt if (tp%lfirst) then - call tp%vh2vb(vbcb = -ptb) + call tp%vh2vb(vbcb = -cb%ptbeg) tp%lfirst = .false. end if - call tp%lindrift(system, dth, ptb) + call tp%lindrift(cb, dth, lbeg=.true.) call tp%accel(system, param, t, lbeg=.true.) call tp%kick(dth) call tp%drift(system, param, dt) call tp%accel(system, param, t + dt, lbeg=.false.) call tp%kick(dth) - call tp%lindrift(system, dth, pte) - call tp%vb2vh(vbcb = -pte) - end associate - end select + call tp%lindrift(cb, dth, lbeg=.false.) + call tp%vb2vh(vbcb = -cb%ptend) + end select + end associate return diff --git a/src/modules/helio_classes.f90 b/src/modules/helio_classes.f90 index 9b88db48d..c95b54397 100644 --- a/src/modules/helio_classes.f90 +++ b/src/modules/helio_classes.f90 @@ -13,12 +13,7 @@ module helio_classes ! helio_nbody_system class definitions and method interfaces !******************************************************************************************************************************** type, public, extends(whm_nbody_system) :: helio_nbody_system - real(DP), dimension(NDIM) :: ptb !! negative barycentric velocity of the central body at the beginning of time step - real(DP), dimension(NDIM) :: pte !! negative barycentric velocity of the central body at the end of time step contains - private - procedure, public :: initialize => helio_setup_system !! Performs Helio-specific initilization steps, - procedure, public :: step => helio_step_system end type helio_nbody_system !******************************************************************************************************************************** @@ -26,6 +21,8 @@ module helio_classes !******************************************************************************************************************************* !> Helio central body particle class type, public, extends(swiftest_cb) :: helio_cb + real(DP), dimension(NDIM) :: ptbeg !! negative barycentric velocity of the central body at the beginning of time step + real(DP), dimension(NDIM) :: ptend !! negative barycentric velocity of the central body at the end of time step contains end type helio_cb @@ -43,7 +40,6 @@ module helio_classes procedure, public :: lindrift => helio_drift_linear_pl !! Method for linear drift of massive bodies due to barycentric momentum of Sun procedure, public :: accel => helio_getacch_pl !! Compute heliocentric accelerations of massive bodies procedure, public :: kick => helio_kickvb_pl !! Kicks the barycentric velocities - procedure, public :: setup => helio_setup_pl !! Constructor method - Allocates space for number of particles procedure, public :: step => helio_step_pl !! Steps the body forward one stepsize end type helio_pl @@ -53,8 +49,6 @@ module helio_classes !! Helio test particle class type, public, extends(swiftest_tp) :: helio_tp - real(DP), dimension(NDIM) :: ptbeg !! negative barycentric velocity of the Sun at beginning of time step - real(DP), dimension(NDIM) :: ptend !! negative barycentric velocity of the Sun at beginning of time step contains procedure, public :: vh2vb => helio_coord_vh2vb_tp !! Convert test particles from heliocentric to barycentric coordinates (velocity only) procedure, public :: vb2vh => helio_coord_vb2vh_tp !! Convert test particles from barycentric to heliocentric coordinates (velocity only) @@ -62,7 +56,6 @@ module helio_classes procedure, public :: lindrift => helio_drift_linear_tp !! Method for linear drift of massive bodies due to barycentric momentum of Sun procedure, public :: accel => helio_getacch_tp !! Compute heliocentric accelerations of massive bodies procedure, public :: kick => helio_kickvb_tp !! Kicks the barycentric velocities - procedure, public :: setup => helio_setup_tp !! Constructor method - Allocates space for number of particles procedure, public :: step => helio_step_tp !! Steps the body forward one stepsize end type helio_tp @@ -111,20 +104,20 @@ module subroutine helio_drift_tp(self, system, param, dt) real(DP), intent(in) :: dt !! Stepsize end subroutine helio_drift_tp - module subroutine helio_drift_linear_pl(self, system, dt, pt) + module subroutine helio_drift_linear_pl(self, cb, dt, lbeg) implicit none - class(helio_pl), intent(inout) :: self !! Helio massive body object - class(helio_nbody_system), intent(in) :: system !! Helio nbody system object - real(DP), intent(in) :: dt !! Stepsize - real(DP), dimension(:), intent(out) :: pt !! negative barycentric velocity of the central body + class(helio_pl), intent(inout) :: self !! Helio massive body object + class(helio_cb), intent(in) :: cb !! Helio central body object + real(DP), intent(in) :: dt !! Stepsize + logical, intent(in) :: lbeg !! Argument that determines whether or not this is the beginning or end of the step end subroutine helio_drift_linear_pl - module subroutine helio_drift_linear_tp(self, system, dt, pt) + module subroutine helio_drift_linear_tp(self, cb, dt, lbeg) implicit none - class(helio_tp), intent(inout) :: self !! Helio test particle object - class(helio_nbody_system), intent(in) :: system !! Helio nbody system object - real(DP), intent(in) :: dt !! Stepsize - real(DP), dimension(:), intent(in) :: pt !! negative barycentric velocity of the Sun + class(helio_tp), intent(inout) :: self !! Helio test particle object + class(helio_cb), intent(in) :: cb !! Helio nbody system object + real(DP), intent(in) :: dt !! Stepsize + logical, intent(in) :: lbeg !! Argument that determines whether or not this is the beginning or end of the step end subroutine helio_drift_linear_tp module subroutine helio_getacch_pl(self, system, param, t, lbeg) @@ -159,25 +152,6 @@ module subroutine helio_kickvb_tp(self, dt) real(DP), intent(in) :: dt !! Stepsize end subroutine helio_kickvb_tp - module subroutine helio_setup_pl(self, n) - implicit none - class(helio_pl), intent(inout) :: self !! Helio massive body object - integer, intent(in) :: n !! Number of test particles to allocate - end subroutine helio_setup_pl - - module subroutine helio_setup_system(self, param) - use swiftest_classes, only : swiftest_parameters - implicit none - class(helio_nbody_system), intent(inout) :: self !! Helio system object - class(swiftest_parameters), intent(inout) :: param !! Current run configuration parameters - end subroutine helio_setup_system - - module subroutine helio_setup_tp(self,n) - implicit none - class(helio_tp), intent(inout) :: self !! Helio test particle object - integer, intent(in) :: n !! Number of test particles to allocate - end subroutine helio_setup_tp - module subroutine helio_step_system(self, param, t, dt) use swiftest_classes, only : swiftest_parameters implicit none diff --git a/src/modules/symba.f90 b/src/modules/symba.f90 index 82ff837a1..209322ee1 100644 --- a/src/modules/symba.f90 +++ b/src/modules/symba.f90 @@ -527,14 +527,14 @@ module subroutine symba_step_helio(lfirst, lextra_force, t, npl, nplm, param%npl end subroutine symba_step_helio module subroutine symba_step_helio_pl(lfirst, lextra_force, t, npl, nplm, param%nplmax, helio_plA, param%j2rp2, param%j4rp4, dt, xbeg, xend, & - ptb, pte) + ptbeg, ptend) implicit none logical , intent(in) :: lextra_force logical , intent(inout) :: lfirst integer(I4B), intent(in) :: npl, nplm, param%nplmax real(DP), intent(in) :: t, param%j2rp2, param%j4rp4, dt real(DP), dimension(npl, NDIMm), intent(out) :: xbeg, xend - real(DP), dimension(NDIM), intent(out) :: ptb, pte + real(DP), dimension(NDIM), intent(out) :: ptbeg, ptend type(helio_pl), intent(inout) :: helio_plA end subroutine symba_step_helio_pl diff --git a/src/symba/symba_step_helio.f90 b/src/symba/symba_step_helio.f90 index 54803c97e..3d3284c0a 100644 --- a/src/symba/symba_step_helio.f90 +++ b/src/symba/symba_step_helio.f90 @@ -9,14 +9,14 @@ use swiftest implicit none logical :: lfirsttp - real(DP), dimension(NDIM) :: ptb, pte + real(DP), dimension(NDIM) :: ptbeg, ptend real(DP), dimension(npl, NDIMm) :: xbeg, xend ! executable code lfirsttp = lfirst - call symba_step_helio_pl(lfirst, lextra_force, t, npl, nplm, param%nplmax, helio_plA, param%j2rp2, param%j4rp4, dt, xbeg, xend, ptb, pte) + call symba_step_helio_pl(lfirst, lextra_force, t, npl, nplm, param%nplmax, helio_plA, param%j2rp2, param%j4rp4, dt, xbeg, xend, ptbeg, ptend) if (ntp > 0) call helio_step_tp(lfirsttp, lextra_force, t, nplm, param%nplmax, ntp, param%ntpmax, helio_plA, helio_tpA, param%j2rp2, param%j4rp4, & - dt, xbeg, xend, ptb, pte) + dt, xbeg, xend, ptbeg, ptend) return diff --git a/src/symba/symba_step_helio_pl.f90 b/src/symba/symba_step_helio_pl.f90 index bf6dd412f..bcf2cfc40 100644 --- a/src/symba/symba_step_helio_pl.f90 +++ b/src/symba/symba_step_helio_pl.f90 @@ -23,7 +23,7 @@ lfirst = .false. end if - call helio_lindrift(npl, helio_plA%swiftest, dth, ptb) + call helio_lindrift(npl, helio_plA%swiftest, dth, ptbeg) call symba_helio_getacch(lflag, lextra_force, t, npl, nplm, param%nplmax, helio_plA, param%j2rp2, param%j4rp4) lflag = .true. @@ -42,7 +42,7 @@ call helio_kickvb(npl, helio_plA, dth) - call helio_lindrift(npl, helio_plA%swiftest, dth, pte) + call helio_lindrift(npl, helio_plA%swiftest, dth, ptend) call coord_vb2vh(npl, helio_plA%swiftest) diff --git a/src/symba/symba_step_interp.f90 b/src/symba/symba_step_interp.f90 index b9832ab53..7ec056ec8 100644 --- a/src/symba/symba_step_interp.f90 +++ b/src/symba/symba_step_interp.f90 @@ -13,7 +13,7 @@ logical , save :: lmalloc = .true. integer( I4B) :: i, irec real(DP) :: dth, msys - real(DP), dimension(NDIM) :: ptb, pte + real(DP), dimension(NDIM) :: ptbeg, ptend real(DP), dimension(:, :), allocatable, save :: xbeg, xend ! executable code @@ -26,10 +26,10 @@ call coord_vh2vb(npl, symba_plA, msys) - call helio_lindrift(npl, symba_plA, dth, ptb) + call helio_lindrift(npl, symba_plA, dth, ptbeg) if (ntp > 0) then - call coord_vh2vb_tp(ntp, symba_tpA, -ptb) - call helio_lindrift_tp(ntp, symba_tpA, dth, ptb) + call coord_vh2vb_tp(ntp, symba_tpA, -ptbeg) + call helio_lindrift_tp(ntp, symba_tpA, dth, ptbeg) do i = 2, npl xbeg(:, i) = symba_plA%xh(:,i) end do @@ -61,10 +61,10 @@ call helio_kickvb(npl, symba_plA, dth) if (ntp > 0) call helio_kickvb_tp(ntp, symba_tpA, dth) call coord_vb2vh(npl, symba_plA) - call helio_lindrift(npl, symba_plA, dth, pte) + call helio_lindrift(npl, symba_plA, dth, ptend) if (ntp > 0) then - call coord_vb2vh_tp(ntp, symba_tpA, -pte) - call helio_lindrift_tp(ntp, symba_tpA, dth, pte) + call coord_vb2vh_tp(ntp, symba_tpA, -ptend) + call helio_lindrift_tp(ntp, symba_tpA, dth, ptend) end if return diff --git a/src/symba/symba_step_interp_eucl.f90 b/src/symba/symba_step_interp_eucl.f90 index 9250e87f2..2036ae9aa 100644 --- a/src/symba/symba_step_interp_eucl.f90 +++ b/src/symba/symba_step_interp_eucl.f90 @@ -12,7 +12,7 @@ logical , save :: lmalloc = .true. integer(I4B) :: i, irec real(DP) :: dth, msys - real(DP), dimension(NDIM) :: ptb, pte + real(DP), dimension(NDIM) :: ptbeg, ptend real(DP), dimension(:, :), allocatable, save :: xbeg, xend ! executable code @@ -25,10 +25,10 @@ call coord_vh2vb(npl, symba_plA, msys) - call helio_lindrift(npl, symba_plA, dth, ptb) + call helio_lindrift(npl, symba_plA, dth, ptbeg) if (ntp > 0) then - call coord_vh2vb_tp(ntp, symba_tpA, -ptb) - call helio_lindrift_tp(ntp, symba_tpA, dth, ptb) + call coord_vh2vb_tp(ntp, symba_tpA, -ptbeg) + call helio_lindrift_tp(ntp, symba_tpA, dth, ptbeg) do i = 2, npl xbeg(:, i) = symba_plA%xh(:,i) end do @@ -61,10 +61,10 @@ call helio_kickvb(npl, symba_plA, dth) if (ntp > 0) call helio_kickvb_tp(ntp, symba_tpA, dth) call coord_vb2vh(npl, symba_plA) - call helio_lindrift(npl, symba_plA, dth, pte) + call helio_lindrift(npl, symba_plA, dth, ptend) if (ntp > 0) then - call coord_vb2vh_tp(ntp, symba_tpA, -pte) - call helio_lindrift_tp(ntp, symba_tpA, dth, pte) + call coord_vb2vh_tp(ntp, symba_tpA, -ptend) + call helio_lindrift_tp(ntp, symba_tpA, dth, ptend) end if return diff --git a/src/whm/whm_getacch.f90 b/src/whm/whm_getacch.f90 index 182b385b9..26a3acb19 100644 --- a/src/whm/whm_getacch.f90 +++ b/src/whm/whm_getacch.f90 @@ -33,9 +33,9 @@ module subroutine whm_getacch_pl(self, system, param, t, lbeg) call whm_getacch_ah3(pl) if (param%loblatecb) then - call cb%set_beg_end(aoblbeg = cb%aobl) + cb%aoblbeg = cb%aobl call pl%accel_obl(system) - call cb%set_beg_end(aoblend = cb%aobl) + cb%aoblend = cb%aobl end if if (param%lextra_force) call pl%accel_user(system, param, t) if (param%lgr) call pl%accel_gr(param) diff --git a/src/whm/whm_step.f90 b/src/whm/whm_step.f90 index 8aa8cfd2a..fb84fe49e 100644 --- a/src/whm/whm_step.f90 +++ b/src/whm/whm_step.f90 @@ -54,7 +54,6 @@ module subroutine whm_step_pl(self, system, param, t, dt) call pl%set_beg_end(xbeg = pl%xh) call pl%kick(dth) call pl%vh2vj(cb) - !If GR enabled, calculate the p4 term before and after each drift if (param%lgr) call pl%p4(param, dth) call pl%drift(system, param, dt) if (param%lgr) call pl%p4(param, dth)