From dffc972677a8eee372991a2bcfc7509cc2765138 Mon Sep 17 00:00:00 2001
From: David A Minton <daminton@purdue.edu>
Date: Mon, 12 Jul 2021 18:15:28 -0400
Subject: [PATCH] Fixed initial conditions generator for RMVS comparison run
 (but now the test particles are not the same

---
 .../9pl_18tp_encounters/cb.swiftest.in        |   4 +-
 .../9pl_18tp_encounters/init_cond.py          | 146 ++----
 .../9pl_18tp_encounters/param.swifter.in      |  52 +-
 .../9pl_18tp_encounters/param.swiftest.in     |  65 +--
 .../9pl_18tp_encounters/pl.swifter.in         |  64 +--
 .../9pl_18tp_encounters/pl.swiftest.in        |  32 +-
 .../swiftest_rmvs_vs_swifter_rmvs.ipynb       | 486 +++++++++++++++---
 examples/whm_gr_test/init_cond.py             |  11 +-
 python/swiftest/swiftest/io.py                |   6 +-
 src/io/io.f90                                 |   1 +
 10 files changed, 564 insertions(+), 303 deletions(-)

diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in
index 0e35c1909..81c636655 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in
@@ -1,5 +1,5 @@
-0.0002959122081920778
-0.0002959122081920778
+0
+0.00029591220819207774
 0.004650467260962157
 4.7535806948127355e-12
 -2.2473967953572827e-18
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py
index 5b5a95bf6..11e04e0f3 100755
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py
@@ -20,67 +20,27 @@
 swiftest_bin   = "bin.swiftest.dat"
 swiftest_enc   = "enc.swiftest.dat"
 
-#Values from JPL Horizons
-AU2M = np.longdouble(const.au.value)
-GMSunSI = np.longdouble(const.GM_sun.value)
-Rsun = np.longdouble(const.R_sun.value)
-GC = np.longdouble(const.G.value)
-JD = 86400
-year = np.longdouble(365.25 * JD)
-c = np.longdouble(299792458.0)
-
-MU2KG    = np.longdouble(GMSunSI / GC) #Conversion from mass unit to kg
-DU2M     = np.longdouble(AU2M)         #Conversion from radius unit to centimeters
-TU2S     = np.longdouble(JD)         #Conversion from time unit to seconds
-GU       = np.longdouble(GC / (DU2M**3 / (MU2KG * TU2S**2)))
-GMSun = np.longdouble(GMSunSI / (DU2M**3 / TU2S**2))
-
-t_0	  = 0 # simulation start time
-deltaT	= 1.00 * JD / TU2S   # simulation step size
-end_sim = year / TU2S # simulation end time
-t_print = deltaT  #output interval to print results
-
-iout = int(np.ceil(t_print / deltaT))
-rmin = Rsun / DU2M
-rmax = 1000.0
-
-sys.stdout = open(swiftest_input, "w")
-print(f'! VERSION      Swiftest input file generated using init_cond.py')
-print(f'T0             {t_0} ')
-print(f'TSTOP          {end_sim}')
-print(f'DT             {deltaT}')
-print(f'CB_IN          {swiftest_cb}')
-print(f'PL_IN          {swiftest_pl}')
-print(f'TP_IN          {tpin}')
-print(f'IN_TYPE        ASCII')
-print(f'ISTEP_OUT      {iout:d}')
-print(f'ISTEP_DUMP     {iout:d}')
-print(f'BIN_OUT        {swiftest_bin}')
-print(f'OUT_TYPE       REAL8')
-print(f'OUT_FORM       XV')
-print(f'OUT_STAT       REPLACE')
-print(f'CHK_CLOSE      yes')
-print(f'CHK_RMIN       {rmin}')
-print(f'CHK_RMAX       {rmax}')
-print(f'CHK_EJECT      {rmax}')
-print(f'CHK_QMIN       {rmin}')
-print(f'CHK_QMIN_COORD HELIO')
-print(f'CHK_QMIN_RANGE {rmin} {rmax}')
-print(f'ENC_OUT        {swiftest_enc}')
-print(f'EXTRA_FORCE    no')
-print(f'BIG_DISCARD    no')
-print(f'ROTATION       no')
-print(f'RHILL_PRESENT  no')
-print(f'GR             no')
-print(f'MU2KG          {MU2KG}')
-print(f'DU2M           {DU2M}')
-print(f'TU2S           {TU2S}')
-sys.stdout = sys.__stdout__
-sim = swiftest.Simulation(param_file=swiftest_input)
-param = sim.param
-
-# Dates to fetch planet ephemerides from JPL Horizons
-tstart = '2021-06-15'
+sim = swiftest.Simulation()
+
+sim.param['T0'] = 0.0
+sim.param['DT'] = 1.0 
+sim.param['TSTOP'] = 365.25
+sim.param['ISTEP_OUT']  = 11
+sim.param['ISTEP_DUMP'] = 1
+sim.param['CHK_QMIN_COORD'] = "HELIO"
+sim.param['CHK_QMIN'] = swiftest.RSun / swiftest.AU2M
+sim.param['CHK_QMIN_RANGE'] = f"{swiftest.RSun / swiftest.AU2M} 1000.0"
+sim.param['CHK_RMIN'] = swiftest.RSun / swiftest.AU2M
+sim.param['CHK_RMAX'] = 1000.0
+sim.param['CHK_EJECT'] = 1000.0
+sim.param['OUT_FORM'] = "XV"
+sim.param['OUT_STAT'] = "UNKNOWN"
+sim.param['GR'] = 'NO'
+sim.param['CHK_CLOSE'] = 'YES'
+
+sim.param['MU2KG'] = swiftest.MSun
+sim.param['TU2S'] = swiftest.JD2S
+sim.param['DU2M'] = swiftest.AU2M
 
 bodyid = {
    "Sun": 0,
@@ -106,7 +66,7 @@
 dims = ['time', 'id', 'vec']
 tp = []
 t = np.array([0.0])
-clab, plab, tlab = swio.make_swiftest_labels(param)
+clab, plab, tlab = swio.make_swiftest_labels(sim.param)
 
 # For each planet, we will initialize a pair of test particles. One on its way in, and one on its way out. We will also initialize two additional particles that don't encounter anything
 tpnames = np.arange(101, 101 + ntp)
@@ -155,50 +115,18 @@
 tpda = xr.concat(tp,dim='time')
 tpds = tpda.to_dataset(dim = 'vec')
 
-ds = xr.combine_by_coords([ds, tpds])
-swio.swiftest_xr2infile(ds, param)
-
-# Swifter PL file
-plfile = open(swifter_pl, 'w')
-print(npl + 1, file=plfile)
-print(0,GMSun,file=plfile)
-print('0.0 0.0 0.0',file=plfile)
-print('0.0 0.0 0.0',file=plfile)
-for i in pl.id:
-    pli = pl.sel(id=i)
-    print(f"{int(i)} {pli['Mass'].values[0]} {pli['Rhill'].values[0]}", file=plfile)
-    print(f"{pli['Radius'].values[0]}", file=plfile)
-    print(f"{pli['px'].values[0]} {pli['py'].values[0]} {pli['pz'].values[0]}", file=plfile)
-    print(f"{pli['vx'].values[0]} {pli['vy'].values[0]} {pli['vz'].values[0]}", file=plfile)
-plfile.close()
-
-# Swifter parameter file
-sys.stdout = open(swifter_input, "w")
-print(f"! VERSION     Swifter input file generated using init_cond.py")
-print(f"T0            {t_0} ")
-print(f"TSTOP         {end_sim}")
-print(f"DT            {deltaT}")
-print(f"PL_IN         {swifter_pl}")
-print(f"TP_IN         {tpin}")
-print(f"IN_TYPE       ASCII")
-print(f"ISTEP_OUT     {iout:d}")
-print(f"ISTEP_DUMP    {iout:d}")
-print(f"BIN_OUT       {swifter_bin}")
-print(f"OUT_TYPE      REAL8")
-print(f"OUT_FORM      XV")
-print(f"OUT_STAT      UNKNOWN")
-print(f"J2            {swiftest.J2Sun}")
-print(f"J4            {swiftest.J4Sun}")
-print(f"CHK_CLOSE     yes")
-print(f"CHK_RMIN      {rmin}")
-print(f"CHK_RMAX      {rmax}")
-print(f"CHK_EJECT     {rmax}")
-print(f"CHK_QMIN      {rmin}")
-print(f"CHK_QMIN_COORD HELIO")
-print(f"CHK_QMIN_RANGE {rmin} {rmax}")
-print(f"ENC_OUT        {swifter_enc}")
-print(f"EXTRA_FORCE    no")
-print(f"BIG_DISCARD    no")
-print(f"RHILL_PRESENT  yes")
-sys.stdout = sys.__stdout__
-
+sim.ds = xr.combine_by_coords([sim.ds, tpds])
+swio.swiftest_xr2infile(sim.ds, sim.param)
+
+sim.param['PL_IN'] = swiftest_pl
+sim.param['TP_IN'] = tpin
+sim.param['CB_IN'] = swiftest_cb
+sim.param['BIN_OUT'] = swiftest_bin
+sim.param['ENC_OUT'] = swiftest_enc
+sim.save(swiftest_input)
+
+sim.param['PL_IN'] = swifter_pl
+sim.param['TP_IN'] = tpin
+sim.param['BIN_OUT'] = swifter_bin
+sim.param['ENC_OUT'] = swifter_enc
+sim.save(swifter_input, codename="Swifter")
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swifter.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swifter.in
index d6a50fc37..ab8bf65ca 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swifter.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swifter.in
@@ -1,26 +1,26 @@
-! VERSION     Swifter input file generated using init_cond.py
-T0            0 
-TSTOP         365.25
-DT            1.0
-PL_IN         pl.swifter.in
-TP_IN         tp.in
-IN_TYPE       ASCII
-ISTEP_OUT     1
-ISTEP_DUMP    1
-BIN_OUT       bin.swifter.dat
-OUT_TYPE      REAL8
-OUT_FORM      XV
-OUT_STAT      UNKNOWN
-J2            2.198e-07
-J4            -4.805e-09
-CHK_CLOSE     yes
-CHK_RMIN      0.004650467260962157
-CHK_RMAX      1000.0
-CHK_EJECT     1000.0
-CHK_QMIN      0.004650467260962157
-CHK_QMIN_COORD HELIO
-CHK_QMIN_RANGE 0.004650467260962157 1000.0
-ENC_OUT        enc.swifter.dat
-EXTRA_FORCE    no
-BIG_DISCARD    no
-RHILL_PRESENT  yes
+! VERSION        Swifter parameter file converted from Swiftest
+T0               0.0
+TSTOP            365.25
+DT               1.0
+ISTEP_OUT        11
+ISTEP_DUMP       1
+OUT_FORM         XV
+OUT_TYPE         REAL8
+OUT_STAT         UNKNOWN
+IN_TYPE          ASCII
+PL_IN            pl.swifter.in
+TP_IN            tp.in
+BIN_OUT          bin.swifter.dat
+ENC_OUT          enc.swifter.dat
+CHK_QMIN         0.004650467260962157
+CHK_RMIN         0.004650467260962157
+CHK_RMAX         1000.0
+CHK_EJECT        1000.0
+CHK_QMIN_COORD   HELIO
+CHK_QMIN_RANGE   0.004650467260962157 1000.0
+EXTRA_FORCE      NO
+BIG_DISCARD      NO
+CHK_CLOSE        YES
+J2               4.7535806948127355e-12
+J4               -2.2473967953572827e-18
+RHILL_PRESENT    YES
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in
index 34f9a5c88..385ac46bb 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in
@@ -1,30 +1,35 @@
-! VERSION      Swiftest input file generated using init_cond.py
-T0             0 
-TSTOP          365.25
-DT             1.0
-CB_IN          cb.swiftest.in
-PL_IN          pl.swiftest.in
-TP_IN          tp.in
-IN_TYPE        ASCII
-ISTEP_OUT      1
-ISTEP_DUMP     1
-BIN_OUT        bin.swiftest.dat
-OUT_TYPE       REAL8
-OUT_FORM       XV
-OUT_STAT       REPLACE
-CHK_CLOSE      yes
-CHK_RMIN       0.004650467260962157
-CHK_RMAX       1000.0
-CHK_EJECT      1000.0
-CHK_QMIN       0.004650467260962157
-CHK_QMIN_COORD HELIO
-CHK_QMIN_RANGE 0.004650467260962157 1000.0
-ENC_OUT        enc.swiftest.dat
-EXTRA_FORCE    no
-BIG_DISCARD    no
-ROTATION       no
-RHILL_PRESENT  no
-GR             no
-MU2KG          1.988409870698051e+30
-DU2M           149597870700.0
-TU2S           86400.0
+! VERSION        Swiftest parameter input
+T0               0.0
+TSTOP            365.25
+DT               1.0
+ISTEP_OUT        11
+ISTEP_DUMP       1
+OUT_FORM         XV
+OUT_TYPE         REAL8
+OUT_STAT         UNKNOWN
+IN_TYPE          ASCII
+PL_IN            pl.swiftest.in
+TP_IN            tp.in
+CB_IN            cb.swiftest.in
+BIN_OUT          bin.swiftest.dat
+ENC_OUT          enc.swiftest.dat
+CHK_QMIN         0.004650467260962157
+CHK_RMIN         0.004650467260962157
+CHK_RMAX         1000.0
+CHK_EJECT        1000.0
+CHK_QMIN_COORD   HELIO
+CHK_QMIN_RANGE   0.004650467260962157 1000.0
+MU2KG            1.988409870698051e+30
+TU2S             86400
+DU2M             149597870700.0
+EXTRA_FORCE      NO
+BIG_DISCARD      NO
+CHK_CLOSE        YES
+FRAGMENTATION    NO
+ROTATION         NO
+TIDES            NO
+ENERGY           NO
+GR               NO
+YARKOVSKY        NO
+YORP             NO
+MTINY            0.0
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in
index 5bed331a6..7961512ca 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in
@@ -2,35 +2,35 @@
 0 0.00029591220819207775568
 0.0 0.0 0.0
 0.0 0.0 0.0
-1 4.9125474498983625e-11 0.0014751244996981092
-1.6306381826061646e-05
-0.3424231950105548 0.04541859803875346 -0.02769885218647143
--0.009135456552973951 0.02914778346055028 0.003219860945895814
-2 7.243452483873647e-10 0.00675910592748785
-4.0453784346544176e-05
--0.7187409324847692 0.008460121607685698 0.04159114061029223
--0.000355507214371255 -0.02031492463311098 -0.0002582876464863964
-3 8.997011382166019e-10 0.010044781409779763
-4.25875607065041e-05
-0.3408913444637776 -0.9577324614296441 4.435598231277718e-05
-0.01592829229600895 0.005704842145070232 -3.222239146362505e-07
-4 9.549535102761465e-11 0.007246745952808949
-2.2657408050928896e-05
--1.518194954784943 0.6839686166809457 0.05157497542651887
--0.005224888295856506 -0.01156432042916445 -0.0001141828894241638
-5 2.825345908631355e-07 0.3552712944567904
-0.0004673261703049093
-4.04554302433205 -2.997516585076586 -0.07806209765007878
-0.004406596292841761 0.006425243736188545 -0.0001252737469736559
-6 8.459715183006416e-08 0.43765252895139073
-0.00038925687730393614
-6.294914485420795 -7.709936089816689 -0.1164782091116569
-0.004015969235853927 0.003521900151979878 -0.000221006899984545
-7 1.2920249163736674e-08 0.46953353749301263
-0.00016953449859497232
-14.85869768503949 13.00480689249104 -0.1442220329069338
--0.002615247360000599 0.002782629142130045 4.407243103045647e-05
-8 1.5243589003230834e-08 0.7812837944287938
-0.00016458790412449367
-29.55697963607957 -4.6325049341728 -0.5858344271811813
-0.0004702098511244648 0.0031273464291932 -7.514820514613305e-05
+1 4.9125474498983623693e-11 0.0014751244996981091688
+1.6306381826061645943e-05
+0.3424231950105547928 0.045418598038753463242 -0.027698852186471431547
+-0.009135456552973951483 0.029147783460550278495 0.003219860945895814102
+2 7.243452483873646905e-10 0.006759105927487850036
+4.0453784346544178454e-05
+-0.7187409324847692238 0.008460121607685697903 0.041591140610292232083
+-0.00035550721437125498313 -0.020314924633110978403 -0.00025828764648639637377
+3 8.9970113821660187435e-10 0.010044781409779763954
+4.25875607065040958e-05
+0.34089134446377761245 -0.95773246142964407746 4.435598231277717939e-05
+0.015928292296008950135 0.005704842145070231768 -3.222239146362504855e-07
+4 9.549535102761465607e-11 0.007246745952808948377
+2.265740805092889601e-05
+-1.5181949547849429294 0.68396861668094566244 0.051574975426518870902
+-0.0052248882958565064094 -0.011564320429164449966 -0.0001141828894241637938
+5 2.825345908631354893e-07 0.35527129445679039879
+0.00046732617030490929307
+4.0455430243320495975 -2.9975165850765859155 -0.07806209765007877943
+0.0044065962928417608604 0.006425243736188544774 -0.00012527374697365590813
+6 8.459715183006415395e-08 0.43765252895139074356
+0.00038925687730393611812
+6.29491448542079457 -7.7099360898166890976 -0.11647820911165690516
+0.004015969235853926976 0.0035219001519798780186 -0.00022100689998454499602
+7 1.2920249163736673626e-08 0.4695335374930126262
+0.00016953449859497231466
+14.8586976850394894 13.004806892491039605 -0.14422203290693380584
+-0.002615247360000599007 0.0027826291421300451516 4.4072431030456472162e-05
+8 1.5243589003230834323e-08 0.78128379442879379807
+0.000164587904124493665
+29.55697963607957135 -4.6325049341728004038 -0.5858344271811812831
+0.00047020985112446482199 0.0031273464291932001093 -7.514820514613305166e-05
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in
index 7aed2bd36..5e89dafc6 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in
@@ -1,33 +1,33 @@
 8
-1 4.9125474498983625056e-11
+1 4.9125474498983623693e-11
 1.6306381826061645943e-05
 0.3424231950105547928 0.045418598038753463242 -0.027698852186471431547
--0.0091354565529739517565 0.029147783460550279367 0.0032198609458958141984
-2 7.243452483873647106e-10
+-0.009135456552973951483 0.029147783460550278495 0.003219860945895814102
+2 7.243452483873646905e-10
 4.0453784346544178454e-05
 -0.7187409324847692238 0.008460121607685697903 0.041591140610292232083
--0.00035550721437125499377 -0.02031492463311097901 -0.0002582876464863963815
-3 8.997011382166018993e-10
+-0.00035550721437125498313 -0.020314924633110978403 -0.00025828764648639637377
+3 8.9970113821660187435e-10
 4.25875607065040958e-05
 0.34089134446377761245 -0.95773246142964407746 4.435598231277717939e-05
-0.015928292296008950611 0.0057048421450702319388 -3.2222391463625049515e-07
-4 9.549535102761465872e-11
+0.015928292296008950135 0.005704842145070231768 -3.222239146362504855e-07
+4 9.549535102761465607e-11
 2.265740805092889601e-05
 -1.5181949547849429294 0.68396861668094566244 0.051574975426518870902
--0.0052248882958565065657 -0.011564320429164450312 -0.000114182889424163797216
-5 2.8253459086313549713e-07
+-0.0052248882958565064094 -0.011564320429164449966 -0.0001141828894241637938
+5 2.825345908631354893e-07
 0.00046732617030490929307
 4.0455430243320495975 -2.9975165850765859155 -0.07806209765007877943
-0.004406596292841760992 0.0064252437361885449665 -0.00012527374697365591187
-6 8.45971518300641563e-08
+0.0044065962928417608604 0.006425243736188544774 -0.00012527374697365590813
+6 8.459715183006415395e-08
 0.00038925687730393611812
 6.29491448542079457 -7.7099360898166890976 -0.11647820911165690516
-0.0040159692358539270963 0.003521900151979878124 -0.00022100689998454500264
-7 1.2920249163736673984e-08
+0.004015969235853926976 0.0035219001519798780186 -0.00022100689998454499602
+7 1.2920249163736673626e-08
 0.00016953449859497231466
 14.8586976850394894 13.004806892491039605 -0.14422203290693380584
--0.0026152473600005990854 0.0027826291421300452348 4.4072431030456473482e-05
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diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
index f57828160..d564f3b97 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
@@ -22,9 +22,9 @@
      "output_type": "stream",
      "text": [
       "Reading Swifter file param.swifter.in\n",
-      "Reading in time 3.660e+02\n",
+      "Reading in time 3.630e+02\n",
       "Creating Dataset\n",
-      "Successfully converted 367 output frames.\n",
+      "Successfully converted 34 output frames.\n",
       "Swifter simulation data stored as xarray DataSet .ds\n"
      ]
     }
@@ -46,9 +46,9 @@
      "output_type": "stream",
      "text": [
       "Reading Swiftest file param.swiftest.in\n",
-      "Reading in time 3.660e+02\n",
+      "Reading in time 3.630e+02\n",
       "Creating Dataset\n",
-      "Successfully converted 367 output frames.\n",
+      "Successfully converted 34 output frames.\n",
       "Swiftest simulation data stored as xarray DataSet .ds\n"
      ]
     }
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+       "       107, 108, 109, 110, 111, 112, 113, 114, 115, 116])\n",
+       "Coordinates:\n",
+       "  * id       (id) int64 1 2 3 4 5 6 7 8 101 ... 109 110 111 112 113 114 115 116</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'id'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>id</span>: 24</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-38ea691e-fa68-4063-b10c-dfd7d4a10e22' class='xr-array-in' type='checkbox' checked><label for='section-38ea691e-fa68-4063-b10c-dfd7d4a10e22' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7 8 101 102 ... 107 108 109 110 111 112 113 114 115 116</span></div><div class='xr-array-data'><pre>array([  1,   2,   3,   4,   5,   6,   7,   8, 101, 102, 103, 104, 105, 106,\n",
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+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])\n",
        "Coordinates:\n",
        "    id        int64 4\n",
-       "  * time (d)  (time (d)) float64 0.0 1.0 2.0 3.0 4.0 ... 363.0 364.0 365.0 366.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'px'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time (d)</span>: 367</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bd19c8eb-96c5-483b-8087-0ed04ffe6631' class='xr-array-in' type='checkbox' checked><label for='section-bd19c8eb-96c5-483b-8087-0ed04ffe6631' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
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-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
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-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></div></li><li class='xr-section-item'><input id='section-d77ca23f-0283-4c99-a479-fde6869293f7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d77ca23f-0283-4c99-a479-fde6869293f7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4</div><input id='attrs-42309245-31db-4111-8f91-6ff4bfab0b4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42309245-31db-4111-8f91-6ff4bfab0b4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e48189a-38e2-488e-b90e-7c7181a17f09' class='xr-var-data-in' type='checkbox'><label for='data-5e48189a-38e2-488e-b90e-7c7181a17f09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time (d)</span></div><div class='xr-var-dims'>(time (d))</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 ... 364.0 365.0 366.0</div><input id='attrs-6b8afc0c-1077-41d4-add3-25b4e4438780' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b8afc0c-1077-41d4-add3-25b4e4438780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78717329-b514-4f79-88b4-57fa03a3230e' class='xr-var-data-in' type='checkbox'><label for='data-78717329-b514-4f79-88b4-57fa03a3230e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0.,   1.,   2., ..., 364., 365., 366.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8a12bfb9-21c9-495e-89c8-439ffb5935d7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8a12bfb9-21c9-495e-89c8-439ffb5935d7' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "  * time (d)  (time (d)) float64 0.0 11.0 22.0 33.0 ... 330.0 341.0 352.0 363.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'px'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time (d)</span>: 34</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0f123cd9-e819-4ef3-a897-d5202b244066' class='xr-array-in' type='checkbox' checked><label for='section-0f123cd9-e819-4ef3-a897-d5202b244066' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></div></li><li class='xr-section-item'><input id='section-deafe412-130b-448e-b219-f5c2076d57b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-deafe412-130b-448e-b219-f5c2076d57b4' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4</div><input id='attrs-f56aa9ca-ad8f-4ab2-897d-066903932c1b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f56aa9ca-ad8f-4ab2-897d-066903932c1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58c2b934-7264-490f-9f25-0a2f8bde2047' class='xr-var-data-in' type='checkbox'><label for='data-58c2b934-7264-490f-9f25-0a2f8bde2047' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time (d)</span></div><div class='xr-var-dims'>(time (d))</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 11.0 22.0 ... 341.0 352.0 363.0</div><input id='attrs-1c129537-6880-4f4f-a786-f9f3e0da1062' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c129537-6880-4f4f-a786-f9f3e0da1062' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f80a2113-dce8-4194-980b-b374d05cc1f8' class='xr-var-data-in' type='checkbox'><label for='data-f80a2113-dce8-4194-980b-b374d05cc1f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0.,  11.,  22.,  33.,  44.,  55.,  66.,  77.,  88.,  99., 110., 121.,\n",
+       "       132., 143., 154., 165., 176., 187., 198., 209., 220., 231., 242., 253.,\n",
+       "       264., 275., 286., 297., 308., 319., 330., 341., 352., 363.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d1987832-8127-4485-9a06-f2d59fef0773' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d1987832-8127-4485-9a06-f2d59fef0773' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
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        "Coordinates:\n",
        "    id        int64 4\n",
-       "  * time (d)  (time (d)) float64 0.0 1.0 2.0 3.0 4.0 ... 363.0 364.0 365.0 366.0"
+       "  * time (d)  (time (d)) float64 0.0 11.0 22.0 33.0 ... 330.0 341.0 352.0 363.0"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -545,12 +871,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -571,12 +897,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -597,7 +923,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -609,7 +935,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -632,7 +958,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -644,7 +970,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
diff --git a/examples/whm_gr_test/init_cond.py b/examples/whm_gr_test/init_cond.py
index de15165c1..ddd4a315c 100755
--- a/examples/whm_gr_test/init_cond.py
+++ b/examples/whm_gr_test/init_cond.py
@@ -2,6 +2,11 @@
 import swiftest
 
 sim = swiftest.Simulation()
+sim.param['PL_IN'] = "pl.swiftest.in"
+sim.param['TP_IN'] = "tp.swiftest.in"
+sim.param['CB_IN'] = "cb.swiftest.in"
+sim.param['BIN_OUT'] = "bin.swiftest.dat"
+sim.param['ENC_OUT'] = "enc.swiftest.dat
 
 sim.param['MU2KG'] = swiftest.MSun
 sim.param['TU2S'] = swiftest.YR2S
@@ -36,11 +41,7 @@
 for name, id in bodyid.items():
    sim.add(name, idval=id)
    
-sim.param['PL_IN'] = "pl.swiftest.in"
-sim.param['TP_IN'] = "tp.swiftest.in"
-sim.param['CB_IN'] = "cb.swiftest.in"
-sim.param['BIN_OUT'] = "bin.swiftest.dat"
-sim.param['ENC_OUT'] = "enc.swiftest.dat"
+"
 sim.save("param.swiftest.in")
 sim.param['PL_IN'] = "pl.swifter.in"
 sim.param['TP_IN'] = "tp.swifter.in"
diff --git a/python/swiftest/swiftest/io.py b/python/swiftest/swiftest/io.py
index 14f137838..ceab9a74f 100644
--- a/python/swiftest/swiftest/io.py
+++ b/python/swiftest/swiftest/io.py
@@ -654,11 +654,12 @@ def swiftest_xr2infile(ds, param, framenum=-1):
     RSun = np.double(cb['Radius'])
     J2 = np.double(cb['J_2'])
     J4 = np.double(cb['J_4'])
+    cbid = int(0)
     
     if param['IN_TYPE'] == 'ASCII':
         # Swiftest Central body file
         cbfile = open(param['CB_IN'], 'w')
-        print(GMSun, file=cbfile)
+        print(0, file=cbfile)
         print(GMSun, file=cbfile)
         print(RSun, file=cbfile)
         print(J2, file=cbfile)
@@ -687,9 +688,8 @@ def swiftest_xr2infile(ds, param, framenum=-1):
     elif param['IN_TYPE'] == 'REAL8':
         # Now make Swiftest files
         cbfile = FortranFile(param['CB_IN'], 'w')
-        MSun = np.double(1.0)
-        cbid = 0
         cbfile.write_record(cbid)
+        MSun = np.double(1.0)
         cbfile.write_record(np.double(GMSun))
         cbfile.write_record(np.double(rmin))
         cbfile.write_record(np.double(J2))
diff --git a/src/io/io.f90 b/src/io/io.f90
index 12fe2cdab..8e8643ac0 100644
--- a/src/io/io.f90
+++ b/src/io/io.f90
@@ -665,6 +665,7 @@ module subroutine io_read_cb_in(self, param)
       is_ascii = (param%in_type == 'ASCII') 
       if (is_ascii) then
          open(unit = iu, file = param%incbfile, status = 'old', form = 'FORMATTED', iostat = ierr)
+         read(iu, *, iostat = ierr) self%id
          read(iu, *, iostat = ierr) val 
          self%Gmass = real(val, kind=DP)
          self%mass = real(val / param%GU, kind=DP)