diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.in
new file mode 100644
index 000000000..c33aa2b5c
--- /dev/null
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.in
@@ -0,0 +1,4 @@
+0.00029591220819207774
+0.004650467260962157
+4.7535806948127355e-12
+-2.2473967953572827e-18
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 689d47628..c33aa2b5c 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/cb.swiftest.in
@@ -1,4 +1,4 @@
-0.0002959122081920778
+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
old mode 100644
new mode 100755
index 314e59420..11e04e0f3
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/init_cond.py
@@ -1,4 +1,6 @@
+#!/usr/bin/env python3
 import numpy as np
+import swiftest
 import swiftest.io as swio
 import astropy.constants as const
 import sys
@@ -18,75 +20,53 @@
 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'GR             no')
-print(f'MU2KG          {MU2KG}')
-print(f'DU2M           {DU2M}')
-print(f'TU2S           {TU2S}')
-sys.stdout = sys.__stdout__
-param = swio.read_swiftest_param(swiftest_input)
-
-# Dates to fetch planet ephemerides from JPL Horizons
-tstart = '2021-06-15'
-ds = swio.solar_system_pl(param, tstart)
+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,
+   "Mercury": 1,
+   "Venus": 2,
+   "Earth": 3,
+   "Mars": 4,
+   "Jupiter": 5,
+   "Saturn": 6,
+   "Uranus": 7,
+   "Neptune": 8,
+}
+
+for name, id in bodyid.items():
+   sim.add(name, idval=id)
+
+ds = sim.ds
 cb = ds.sel(id=0)
 pl = ds.where(ds.id > 0, drop=True)
 npl = pl.id.size
 
-ntp = 18
+ntp = 16
 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)
@@ -135,50 +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            {param['J2']}")
-print(f"J4            {param['J4']}")
-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 ec31caa63..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 @@
-! 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            4.7535806948127355e-12
-J4            -2.2473967953572827e-18
-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 fff05bacf..385ac46bb 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/param.swiftest.in
@@ -1,29 +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
-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.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.in
new file mode 100644
index 000000000..bd980fc4b
--- /dev/null
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.in
@@ -0,0 +1,33 @@
+8
+1 4.9125474498983623693e-11
+1.6306381826061645943e-05
+0.33206272695596028566 0.07436707001147663254 -0.02438290851908785084
+-0.0115920916602103591525 0.028710618792657981169 0.0034094833969203438596
+2 7.243452483873646905e-10
+4.0453784346544178454e-05
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+0.00021427347881133320621 -0.020313576971905909774 -0.00029114855617710840843
+3 8.9970113821660187435e-10
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+0.35677088372527121507 -0.95189300879814897627 4.4027442504036787155e-05
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+4 9.549535102761465607e-11
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+5 2.825345908631354893e-07
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+6 8.459715183006415395e-08
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+0.0040140666547768266703 0.0035242303011843410798 -0.00022097170940726839814
+7 1.2920249163736673626e-08
+0.00016953449859497231466
+14.856082147529010129 13.007589275314199284 -0.14417795763685259391
+-0.0026158276515510360365 0.0027821364817078499815 4.40781085949555924e-05
+8 1.5243589003230834323e-08
+0.000164587904124493665
+29.55744967800954015 -4.629377558152945049 -0.58590957207831262377
+0.00046987400245862169295 0.0031274056019462009859 -7.51415892482447254e-05
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 f02f6bc6f..701e9a14f 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swifter.in
@@ -1,40 +1,36 @@
-10
-0 0.00029591220819207776388
+9
+0 0.00029591220819207775568
 0.0 0.0 0.0
 0.0 0.0 0.0
-1 4.9125474498983625e-11 0.0014751258227142052
-1.6306381826061646e-05
-0.008059842448018334 -0.4616051037329109 -0.03846017738329229
-0.02248719132054853 0.001934639213990692 -0.001904656977422976
-2 7.243452483873647e-10 0.006759134232034941
-4.0453784346544176e-05
--0.5115875215389065 0.5030818749037324 0.03642547299277956
--0.01425515725454357 -0.01452868630179309 0.0006232072038298823
-3 8.997011382166019e-10 0.010044625087011915
-4.25875607065041e-05
--0.1090020607540907 -1.009893805009766 4.823302918632528e-05
-0.01682491922568941 -0.001910549762056979 3.992660742687128e-08
-4 9.549535102761465e-11 0.0072467897902424765
-2.2657408050928896e-05
--1.342897929331636 0.9778655112682739 0.05343398538723887
--0.007712315645393206 -0.01011917844182223 -2.287744801261131e-05
-5 2.825345908631355e-07 0.3552720805286442
-0.0004673261703049093
-3.923184193414315 -3.168419770483168 -0.0746147877972047
-0.004655552638985802 0.006232623300954468 -0.0001300429201057457
-6 8.459715183006416e-08 0.4376460836930155
-0.00038925687730393614
-6.185794462795267 -7.804174837804826 -0.110498432926239
-0.004066833203985018 0.003458637040736611 -0.0002219310939327014
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-0.00016953449859497232
-14.9290976575471 12.92949673572929 -0.1454099139559955
--0.002599557960646664 0.002795888198858545 4.391864857782088e-05
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+-0.0026158276515510360365 0.0027821364817078499815 4.40781085949555924e-05
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+0.000164587904124493665
+29.55744967800954015 -4.629377558152945049 -0.58590957207831262377
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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 0920f9b2e..bd980fc4b 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/pl.swiftest.in
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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..4c742df8c 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
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      "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"
      ]
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      "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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+       "  * 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-799f0e0f-2ec9-4619-99b2-8786300bea0b' class='xr-array-in' type='checkbox' checked><label for='section-799f0e0f-2ec9-4619-99b2-8786300bea0b' 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",
-       "       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.,\n",
-       "       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.,\n",
-       "       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.,\n",
-       "       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.])\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"
+       "  * time (d)  (time (d)) float64 0.0 11.0 22.0 33.0 ... 330.0 341.0 352.0 363.0"
       ]
      },
      "execution_count": 8,
@@ -550,7 +492,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -576,7 +518,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -609,7 +551,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -644,7 +586,7 @@
     },
     {
      "data": {
-      "image/png": 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lUxZO+GbWVv0KqG7hl4MTvpm1FRMp43uUTjk44ZtZW7VaSvhyC78UnPDNrK16wneXTjk44ZtZW+7SKRcnfDNryy38cnHCN7O2ahPuwy8TF08zs7ZqtRrrfv9Tlp13ITdetvGgw+mriMHVR95ks8057B9O6Pl6nfDNrK2oBeseW87D948zf+PtBheIBvcLQwOoj7xu/vw5Wa8Tvpm1lbp0Jth+j/35sxPeM+hwbJbch29mbUUt/aNxtw3LwAnfzNpKo3RqjM8bH3Qo1gNO+GbWVtRSl86YW/il4IRvZm2tWzsBwLgTfik44ZtZWxNr1wIwPt8Jvwz6nvAljUu6WtL5/d62mRVTT/ju0imHQbTw3w3cOIDtmllB6yZb+D5oWwZ9TfiSdgD+BDitn9s1s+5MrFsHwPj43JwIZP3V7xb+p4DjgVqft2tmXVj3eEr4Y/PcpVMGfUv4kl4BrIyIq2ZY7mhJyyQtW7VqVZ+iM7NWarmFP89dOqXQzxb+AcCfSroN+Crwx5LObl4oIpZExOKIWLxw4cI+hmdmzdatcwu/TPqW8CPifRGxQ0QsAl4PXBIRb+rX9s2suIm1uYU/z334ZeBx+GbW1uRBW4/DL4WBvIsRsRRYOohtm1nnnPDLxS18M2vLCb9cnPDNrK3aOtfSKRMnfDNrq7Yun2m7kRN+GTjhm1lbExOphT/PwzJLwQnfzNqqD8sc38jDMsvACd/M2qpN1M+0dcIvAyd8M2urVu/S8SidUnDCN7O2Jodl+qBtKTjhm1lb9S6dcR+0LQUnfDNra3IcvhN+KTjhm1lbUy18H7QtAyd8M2tropZa+GPzXA+/DJzwzaytyF06voh5OTjhm1lbtVr9mrZu4ZeBE76ZtZVKKwiNOVWUgd9FM2srJtaBnCbKwu+kmbVVq00g3J1TFk74ZtZWTEyAnPDLwgnfzNqq1SaQu3RKw++kmbUVNbfwy8QJ38zaqk24hV8mfifNrK2ICTTmFn5Z+PS5EphYW+O6H93F2scmNpgnrfdovf82nF+f1mpi490N1zOTVqvshZax9mzlReKYmxXP3X7rbLnHH33cLfwSccIvgftu+x8u/8ZNgw7DSmjto2vZaGOnibLwO1kCjz/6GOt+/3N2e/YT2XyrTSBisuUbNLSCg6nGZdCwTKQmX6RZkup3p1rz5Oc2rmOD+U3LNm1n/RlN01v9EmlaZ9tFZvrJMu12O2vqFmiT5/9j2qUmt93BYh0v17j5HrnukrVsvOkWvV2pDYwTfgk8cNctrHv0J/zq8rGGn99TGSIimielJD+1wNwHaSNrt/2eN+gQrEec8EugXrP8xW97P3u/dP+erTei9ZfC+l8WbZZf7wtnvZW2WEeb9bVZZv3vpxZfbB2vZw6+6Dpc51xsu9A6Cyz7hC0XFA/GhpITfhnUP7s9LnDVrutjDg+TmtkcmjHhS9qpw3WtjoiHZxmPdaFWqwFzN6LDzMqhkxb+mWxwqG4DAZwBnNWDmKyg+k95l7A1s+nMmPAj4qDmaZKeHBH3zk1IVlgtJ3w38c1sGt02Cf+yp1HYrNQPSo6NOeGbWXvdHrQ9XNLvgIsjYkUvA7Liot6H7y4dM5tGtxniz4CbgFdJOq2H8VgX6iPs3KVjZtPpqoUfEfcBF+abDdhUC98J38za66qFL+kzks7I91/W4XM2kfRzSddIukHSh7rZtm1ocpSOi1yZ2TS6zRCPA7fk+3/c4XMeA/44IvYG9gEOkdS700IrbCrhu4VvZu11e9D2d8CWkuYDHZ2YFSkr/TY/nJ9vLuLSA+7SMbNOdNvCfxC4GfgMcHmnT5I0Lmk5sJI0wudnLZY5WtIySctWrVrVZXhVUz/xygnfzNor1MKXtAD4JLAHcDbpzNojO31+REwA++T1nCtpz4i4vmmZJcASgMWLF/sXQAei5jNtzbpx93W3sfq+BwcdxgbmzZ/H7i/cq/frLbJwRKyWdCqwCLgf2Av4VtGN5vUsBQ4Brp9hcZtBvQ9/zH34Zh2bWDfBF75xFhOqDTqUDWzKRrx30Ak/OxK4NSIuAq7q9EmSFgJrc7LfFHgJ8NEutm9NJsviepSOWcdiosaEauy59a7s+4JnDzqc9YyNz811hLtJ+A8B75C0B3ANsDwiru7gedsCZ0oaJx07+FpEnN/F9q1J/aCte3TMOlfvCl3wBwt46j57DDia/iic8CPiFEk/BH5NGl55IDBjwo+Ia4FnFd2ezSzmqB6+WZnVy4pX6QIPhRO+pJOAcWA5qXW/tMcxWUERuYXvPnyzjtVb+GMV6got/Eoj4oOkk6jGgFdL+o+eR2WFTPbhe1imWcfqDaUqtZO6/Wo7HXg6sDXw2d6FY12pj9Jxl45Zx+ot/Cpl/G4zxLtI3UHzgE/3LhzrxtQ4/Or84ZrNWgUvHNRtwr8Z2AT4TkQc2MN4rAtT4/DdwjfrVBVrUHWbIW4ALgGOlHRlD+OxLrgP36y4Wr2FP+A4+qnb4mm7kMbjL8n/2yDVR+m4D9+sY5MHbSv0uek24d8ZEZdI2pZUCM0GyFe8Misu3IffsUMk7QB8nlRMzQbI5ZHNiovJEjrV+dx0m/AXAO8FjieNybcBCg/LNCusiuPwu+3SOQl4WkSskDTRy4CsuKniaRX6yzWbpSo2lDp+pZL2rt+PiLsi4gf5/glzEZgVMPmH64Rv1ql6V2iVFPlqu1rStZKOl7TjnEVkhU0Ny6xOS8Vstqp4wmKRDPFxYDPgVOBWSZdKetvchGVFhFv4ZoVVcXRbxwk/Io6LiF2AxcBppLLIS+YqMOvc1MGn6vzhms1W/XNTpWNfHR+0lbQ18Crgz4GDSGOZ7pijuKyIektl3F06Zp2q4jj8IqN07iX9IngI+CJwdkT8ZE6iskIm6+FXaDyx2WxV8VrQRRL+ucDZwPciYu0cxWPdqB+zdQvfrGNVPGjbccKPiNfOZSDWvSr2RZrN1tSwzOp8btwkLIHJn6bj1fnDNeuVKvXhF074kg6bi0Cse1Nn2vr726xTVezS6SZDnNzzKGx2Jvvwq/OHazZbtVr1hjN3k/Crs3dGxOQoHbfwzTrnE686Ej2PwmbFxdPMivMlDm0kVfEP12y2wl06NpIicE+bWTFTYx2q89npJuHf1/MobFYmu3TMrGP1g7ZV6gotnPAj4qVzEYjNglv4ZoVNnr8y4Dj6qUqvtbTCCd+suMkuneqkweq80hJzwjcrroplxbtK+JLe03B/j96FY11xH75ZYfUzbavUh1/oIuaSFgCfBJ4m6VHgWuBI4K29D806FRGV+qM164XJ4cwVGqVTKOFHxGrgrZIOBu4H9gK+NQdxWQEepWNWnOvhd25tRFwl6W5gZS8Dsm64D9+sqMkTryrUwu/2oO0hknYAPk/q4pmRpB3zhc9vlHSDpHd3uW1r4oO2Zl2o/zCuUAu/24S/AHgvcDzwWIfPWQccExFPB/YH/lbSM7rcvjWKQE74ZoVMlSSpzmDFbrt0TgL2iIgVkiY6eUJE3APck++vkXQjsD3wyy5jsCwdtB10FGajZapLZ8CB9FG3L/V9wBH5/qVFnyxpEfAs4Gct5h0taZmkZatWreoyvIpxl45ZYbXJsQ7V+ex0m/AfB27J9w8q8kRJmwPfBP4+Ih5unh8RSyJicUQsXrhwYZfhVYv78M26kUfp+EzbGf0O2FLSfGCnTp+Ul/8mcE5EeDhnzzjhmxXlSxx27p+Am4HPAOd08gSl85e/ANwYEZ/ocrvWgvvwzYqbTPgVGqXT7UHbd9WTdoHSCgeQ+v2vk7Q8T3t/RFzQZQxW5y4ds8ICJ/xp5dIKnwN2zqUVrgH+ig5KK0TET3BWmhPhYZlmhbm0wgwiYrWku4DLSCNs9salFQbPtXTMCqviJQ676dJ5AHgHsAephX9XTyOywlxLx6y4Kl7isHDCj4hTJV0C/BrYB3gBcHWP47JC3IdvVpTPtO2ApJOAcWA5sDwilvY4JivI5ZHNipv8ZVydfN9VC/+Dkp5EOlP21ZJ2iYijeh+aFeGDtmYFhUfpdOrtwL9HxIW9DMa6U79Um5l1rjZZD786TfxuE/7pwF9L2ox01uzy3oVkhQXu0jEryGfadu5dpC+LecC/9i4c64Zr6Zh1o3rXtO024d8MbAJ8JyIO7GE81hWfeGVWVBVPvOo24d8AXAIcKenKHsZjXXAtHbPiprp03Ic/k12Ah4Al+X8bJHfpmHWtQj06XSf8OyPiEknb4ouYD1zgcfhmRdVyaYUxd+nMqPBFzG0OuXiaWWFTpRWq06XTz4uY21xxl45ZF6pXg6rjhC9p74aHJ5FG6KwAOrqIuc0dd+mYFedROtO7WtK1ko4HFBE/AIiIE+YmNOtYhNv3ZgVNlkd2l05LHwc2A04FbpV0qaS3zU1YVkSAW/hmBU3WTqvQZ6fjhB8Rx0XELsBi4DTgQNKwTBs09+GbFTZ5icMKtfA7HpYpaWvgVcCfAweRMswdcxSXFRARlar4Z9YLVezDLzIO/17SL4KHgC8CZ+fr1NrAuYVvVtjkuMzBhtFPRRL+ucDZwPciYu0cxWPdiJr78M0KquI4/BkTvqSd8t1j8//btuk+WB0RD/cqMOuc2/dmxdWiemfadtLCP5OpMxTa7ZkAzgDO6kFMVpQvcWhWnFv4G4qIg/oRiM2G2/hmRUUFL3FYna+2EvNFzM2KmxqlU500WJ1XWmbhi5ibFVXFYZlO+KXgUTpmxVVvWKYTfgn4GuZmxdXqpRXcpWMjJQK/lWYFRQ1VrEKys0Qp+Jq2ZkWlLvxqfXCc8EvAtXTMiosKlhV3wi+Nqv3pms1OVPDSoE74ZeAWvllhFeu+B5zwS8Jn2poVFrXKfWr6lvAlnS5ppaTr+7XNqnAfvllxUcETFvvZwj8DOKSP26sQl1YwKyoq2KnTt4QfEZcBD/Zre9VSvYNPZrNVxV/GQ9eHL+loScskLVu1atWgwxkNPtXWrDgPyxy8iFgSEYsjYvHChQsHHc5ICHfpmBXmE69sNFWwpWI2W0H1PjdO+KUQIL+VZkX4xKs5JOkrwBXAHpLuknRkv7ZdBe7RMSsmKnj+SifXtO2JiPiLfm2ratJoA7fwzQqpYM1BZ4lSqN54YrPZqlXw2JcTfil4lI5ZYe7Dt5EUVO4EErPZquLvYif8UnAL36yoiFrlGkpO+CUQLq1g1pWqfW6c8EshYKxaf7hmsxVRvU4dJ/wyqGCZV7PZ8olXNqKqV/XPbLaCqNyhLyf8UvBBW7OiXDzNRpRb+GbF+cQrG0Wuh29WmPvwbSR5WKZZcdUbo+OEXxLu0jErypc4tBHlg7ZmRVXxl7ETfklUraViNmsuj2wjKdzCNyuqiteCdsIvCbfwzYrxKB0bUdU7+GTWC1X71Djhl0L1fpqazVYqnlatz40TfilU76ep2Wy5lo6NLI35rTQrIrXvq5XxnSVKoYrnDJrNUriFbyOmVqsBHqVjVpRPvLLRU8uteyd8s0KigkUHnfBHXC1357gP36yYcHlkGzW1idylM+A4zEZNVPDSoE74o65+IWa38M0Kqt4Ji84SI26yhV+tv1uzWavi2DYn/FGXW/iS30qzIsItfBs1tfoonYr1RZrNmoun2aipj8MfG6vWH67ZbKVRmdX63Djhjzq38M26EhXsxXfCH3G1eh++W/hmhfiatjZypkbpVOsP16wX3Ic/hyQdImmFpJskndDPbZdWuLSCWTeqWB55Xr82JGkc+AzwUuAu4EpJ50XEL/sVQxm5eNos1L8s6//T+Hi6eZnG0hetxqbul0VEvtXSjYb7G0zPjxGMjcPYvIbb+PDsl8nXNAFRyxdAAR59eOr11Cagtm7qFrX1H9fWQa1h2tg4jM2H8frrnQ/j89P9+v+N95vjWX9Cw33BRk/o+S7oW8IHngPcFBG3AEj6KnA40POE/6kPfJSaqnNARrsfwK9X3c0n/88/DzoUs5GxZmwtm696jAtesf+gQ9nAA1tvzBH//+qer7efCX974M6Gx3cB+zUvJOlo4GiAnXbaqasNbToxRq2rZ44mAWOxDm3QYjCzdjZnHlvf85tBh9FX/Uz4rX7XbZChImIJsARg8eLFXWWwt59yXDdPMzMrtX4etL0L2LHh8Q7A3X3cvplZpfUz4V8J7CbpKZI2Al4PnNfH7ZuZVVrfunQiYp2kdwIXAePA6RFxQ7+2b2ZWdf3swyciLgAu6Oc2zcws8Zm2ZmYV4YRvZlYRTvhmZhXhhG9mVhGKIT47U9Iq4PYun74NcH8Pw5kLoxAjOM5eGoUYYTTiHIUYof9x7hwRC1vNGOqEPxuSlkXE4kHHMZ1RiBEcZy+NQowwGnGOQowwXHG6S8fMrCKc8M3MKqLMCX/JoAPowCjECI6zl0YhRhiNOEchRhiiOEvbh29mZusrcwvfzMwaOOGbmVVE6RL+MF8oXdJtkq6TtFzSsjxtK0kXS/pN/v+JA4jrdEkrJV3fMK1tXJLel/fvCkkHDzDGEyX9d96fyyUdOuAYd5R0qaQbJd0g6d15+rDty3ZxDs3+lLSJpJ9LuibH+KE8fdj2Zbs4h2ZfriciSnMjlV2+GXgqsBFwDfCMQcfVEN9twDZN0/4FOCHfPwH46ADiOhDYF7h+priAZ+T9ujHwlLy/xwcU44nAsS2WHVSM2wL75vtbAL/OsQzbvmwX59DsT9IV8jbP9+cDPwP2H8J92S7OodmXjbeytfAnL5QeEY8D9QulD7PDgTPz/TOBV/Y7gIi4DHiwaXK7uA4HvhoRj0XErcBNpP0+iBjbGVSM90TEL/L9NcCNpGs5D9u+bBdnO32PM5Lf5ofz8y0Yvn3ZLs52BhJnXdkSfqsLpU/3h9xvAXxf0lX5Yu0AT4qIeyB9EIE/HFh062sX17Dt43dKujZ3+dR/3g88RkmLgGeRWnxDuy+b4oQh2p+SxiUtB1YCF0fEUO7LNnHCEO3LurIl/I4ulD5AB0TEvsDLgb+VdOCgA+rCMO3jzwG7APsA9wAfz9MHGqOkzYFvAn8fEQ9Pt2iLaYOMc6j2Z0RMRMQ+pOtfP0fSntMsPrB92SbOodqXdWVL+EN9ofSIuDv/vxI4l/RT7j5J2wLk/1cOLsL1tItraPZxRNyXP2w14D+Y+mk8sBglzScl0XMi4lt58tDty1ZxDuP+zHGtBpYChzCE+7KuMc5h3ZdlS/hDe6F0SZtJ2qJ+H3gZcD0pvjfnxd4MfGcwEW6gXVznAa+XtLGkpwC7AT8fQHz1D3zdq0j7EwYUoyQBXwBujIhPNMwaqn3ZLs5h2p+SFkpakO9vCrwE+BXDty9bxjlM+3I9/To63K8bcChp1MHNwD8OOp6GuJ5KOjp/DXBDPTZga+CHwG/y/1sNILavkH52riW1QI6cLi7gH/P+XQG8fIAxfgm4DriW9EHadsAxPp/08/xaYHm+HTqE+7JdnEOzP4G9gKtzLNcDH8zTh21ftotzaPZl482lFczMKqJsXTpmZtaGE76ZWUU44ZuZVYQTvplZRTjhm5lVhBO+VYKkBZL+puHxdpK+MUfbeqWkD7aZ99v8/0JJF87F9s3accK3qlgATCb8iLg7Iv58jrZ1PPDZ6RaIiFXAPZIOmKMYzDbghG9VcSqwS65N/jFJi5Rr60t6i6RvS/qupFslvVPSeyRdLemnkrbKy+0i6cJc/O7Hkp7WvBFJuwOPRcT9+fFTJF0h6UpJH25a/NvAG+f0VZs1cMK3qjgBuDki9omI41rM3xN4A6nmycnA7yLiWcAVwF/mZZYAfxcRfwQcS+tW/AHALxoefxr4XEQ8G7i3adllwAu6fD1mhc0bdABmQ+LSSLXh10j6H+C7efp1wF65suTzgK+nUjRAuohFs22BVQ2PDwBene9/Cfhow7yVwHa9Cd9sZk74ZsljDfdrDY9rpM/JGLA6Uhnc6fwe2LJpWrv6JZvk5c36wl06VhVrSJfz60qkevG3SnoNpIqTkvZuseiNwK4Njy8nVW2FDfvrd2eqiqLZnHPCt0qIiAeAyyVdL+ljXa7mjcCRkuoVT1tdPvMy4Fma6vd5N+liN1eyYcv/IOA/u4zFrDBXyzTrMUmfBr4bET+YYbnLgMMj4qH+RGZV5xa+We/9M/CE6RaQtBD4hJO99ZNb+GZmFeEWvplZRTjhm5lVhBO+mVlFOOGbmVWEE76ZWUX8L2BhAUMVl1GAAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
diff --git a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/tp.in b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/tp.in
index 6ae12da23..c7cf002d6 100644
--- a/examples/rmvs_swifter_comparison/9pl_18tp_encounters/tp.in
+++ b/examples/rmvs_swifter_comparison/9pl_18tp_encounters/tp.in
@@ -1,55 +1,49 @@
-18
+16
 101
-0.0080829031543499848395 -0.46158204302657929174 -0.038460177383292291908
-0.025090740792557679473 0.00193463921399069207 -0.0019046569774229759036
+0.33208578766229190915 0.07439013071780828379 -0.02438290851908785084
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 102
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 103
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 104
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 105
--0.10894183284815117663 -1.0098335771038264852 4.8233029186325282966e-05
-0.023719359459963285097 -0.0019105497620569790364 3.9926607426871281197e-08
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 106
--0.109062288660030232146 -1.009954032915705735 4.8233029186325282966e-05
-0.00993047899141553253 -0.0019105497620569790364 3.9926607426871281197e-08
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 107
--1.3428658869178822233 0.97789755368202779806 0.053433985387238869258
--0.0046328365471693128824 -0.01011917844182222935 -2.28774480126113111e-05
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 108
--1.3429299717453899721 0.97783346885452004926 0.053433985387238869258
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 109
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 110
-3.9225232944062176088 -3.169080669491265212 -0.07461478779720470689
--0.03222666456266162771 0.0062326233009544675795 -0.00013004292010574568976
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 111
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 112
-6.1852439704401360743 -7.80472533015995662 -0.11049843292623899582
--0.018046335679548570347 0.0034586370407366112158 -0.00022193109393270140663
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 113
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-0.010495205578015229936 0.0027958881988585449277 4.3918648577820880246e-05
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 114
-14.928857899559897504 12.9292569777420869315 -0.14540991395599550673
--0.015694321499308556966 0.0027958881988585449277 4.3918648577820880246e-05
+14.855842389541807691 13.007349517326996846 -0.14417795763685259391
+-0.015710591190212928187 0.0027821364817078499815 4.40781085949555924e-05
 115
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 116
-29.543928927807161955 -4.717154366160452028 -0.58380301744279916587
--0.013956372192325811402 0.0031257375729174499863 -7.532640451995010599e-05
-117
-14.544494696107316045 -31.052223962419365222 -0.88280002656255951443
-0.0037110399802695879026 0.00066259169021535256356 -0.0009142553677224461283
-118
-14.544472229076623293 -31.052246429450054421 -0.88280002656255951443
-0.002135115255113890012 0.00066259169021535256356 -0.0009142553677224461283
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+-0.0139657618108195089035 0.0031274056019462009859 -7.51415892482447254e-05
diff --git a/src/modules/symba.f90 b/src/modules/symba.f90
index 209322ee1..bb86131f8 100644
--- a/src/modules/symba.f90
+++ b/src/modules/symba.f90
@@ -8,10 +8,10 @@ module symba
    use helio
    implicit none
 
-   integer(I4B), public, parameter :: NENMAX = 32767
-   integer(I4B), public, parameter :: NTENC = 3
-   real(DP), public, parameter     :: RHSCALE = 6.5_DP
-   real(DP), public, parameter     :: RSHELL = 0.48075_DP
+   !integer(I4B), public, parameter :: NENMAX = 32767
+   !integer(I4B), public, parameter :: NTENC = 3
+   !real(DP), public, parameter     :: RHSCALE = 6.5_DP
+   !real(DP), public, parameter     :: RSHELL = 0.48075_DP
 
    !********************************************************************************************************************************
    !                                    symba_tp class definitions and method interfaces