diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.in
index 81c636655..2df47f957 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.in
@@ -1,4 +1,4 @@
-0
+Sun
 0.00029591220819207774
 0.004650467260962157
 4.7535806948127355e-12
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.swiftest.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.swiftest.in
index 81c636655..2df47f957 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.swiftest.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/cb.swiftest.in
@@ -1,4 +1,4 @@
-0
+Sun
 0.00029591220819207774
 0.004650467260962157
 4.7535806948127355e-12
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/init_cond.py b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/init_cond.py
index 5fc0ef7d0..e7420c9f0 100755
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/init_cond.py
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/init_cond.py
@@ -17,7 +17,7 @@
 swiftest_input = "param.swiftest.in"
 swiftest_pl    = "pl.swiftest.in"
 swiftest_cb    = "cb.swiftest.in"
-swiftest_bin   = "bin.swiftest.dat"
+swiftest_bin   = "bin.swiftest.nc"
 swiftest_enc   = "enc.swiftest.dat"
 swiftest_disc  = "discard.swiftest.out"
 
@@ -27,14 +27,13 @@
 sim.param['DT'] = 1.0 
 sim.param['TSTOP'] = 365.25e2
 sim.param['ISTEP_OUT']  = 10
-sim.param['ISTEP_DUMP'] = 10
 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['IN_FORM'] = "XV"
 sim.param['OUT_STAT'] = "UNKNOWN"
 sim.param['GR'] = 'NO'
 sim.param['CHK_CLOSE'] = 'YES'
@@ -68,10 +67,11 @@
 dims = ['time', 'id', 'vec']
 tp = []
 t = np.array([0.0])
+sim.param['OUT_FORM'] = "XV"
 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)
+tpnames = np.arange(npl + 1, npl + 1 + ntp)
 tpxv1 = np.empty((6))
 tpxv2 = np.empty((6))
 
@@ -120,6 +120,7 @@
 sim.ds = xr.combine_by_coords([sim.ds, tpds])
 swio.swiftest_xr2infile(sim.ds, sim.param)
 
+sim.param['ISTEP_DUMP'] = 1000
 sim.param['PL_IN'] = swiftest_pl
 sim.param['TP_IN'] = tpin
 sim.param['CB_IN'] = swiftest_cb
@@ -128,6 +129,7 @@
 sim.param['DISCARD_OUT'] = swiftest_disc
 sim.save(swiftest_input)
 
+sim.param['ISTEP_DUMP'] = 10
 sim.param['PL_IN'] = swifter_pl
 sim.param['TP_IN'] = tpin
 sim.param['BIN_OUT'] = swifter_bin
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swifter.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swifter.in
index acd0bd0ce..741d5ac99 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swifter.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swifter.in
@@ -1,9 +1,9 @@
 ! VERSION        Swifter parameter file converted from Swiftest
 T0               0.0
-TSTOP            9500.0
+TSTOP            36525.0
 DT               1.0
-ISTEP_OUT        100
-ISTEP_DUMP       100
+ISTEP_OUT        10
+ISTEP_DUMP       10
 OUT_FORM         XV
 OUT_TYPE         REAL8
 OUT_STAT         UNKNOWN
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swiftest.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swiftest.in
index f924ebb95..8fe2397a0 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swiftest.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/param.swiftest.in
@@ -1,17 +1,17 @@
 ! VERSION        Swiftest parameter input
 T0               0.0
-TSTOP            9500.0
+TSTOP            36525.0
 DT               1.0
-ISTEP_OUT        100
-ISTEP_DUMP       100
+ISTEP_OUT        10
+ISTEP_DUMP       1000
 OUT_FORM         XV
-OUT_TYPE         REAL8
+OUT_TYPE         NETCDF_DOUBLE
 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
+BIN_OUT          bin.swiftest.nc
 CHK_QMIN         0.004650467260962157
 CHK_RMIN         0.004650467260962157
 CHK_RMAX         1000.0
@@ -21,6 +21,7 @@ CHK_QMIN_RANGE   0.004650467260962157 1000.0
 MU2KG            1.988409870698051e+30
 TU2S             86400
 DU2M             149597870700.0
+IN_FORM          XV
 ENC_OUT          enc.swiftest.dat
 EXTRA_FORCE      NO
 DISCARD_OUT      discard.swiftest.out
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.in
index e506d4743..02e5eadf9 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.in
@@ -1,33 +1,33 @@
 8
-1 4.9125474498983623693e-11 0.0014751244935834097723
+Mercury 4.9125474498983623693e-11 0.0014751310862809727629
 1.6306381826061645943e-05
--0.37723213134178928962 0.033583006382262102496 0.037347605390151236704
--0.008342765357522348782 -0.026815373891535949219 -0.0014259978126226569104
-2 7.243452483873646905e-10 0.006759064884572926305
+0.3145650549772632254 -0.2555573396958932264 -0.04973776595957409008
+0.012185837286798669593 0.023148338651330341298 0.0007738432831418731988
+Venus 7.243452483873646905e-10 0.006759109593536554028
 4.0453784346544178454e-05
--0.48772324783973242113 -0.53438159383885197595 0.020810210727290629623
-0.014797158412775200664 -0.013730742274988789325 -0.0010423161661001279551
-3 8.9970113821660187435e-10 0.01004492566381686821
+0.387431535393453097 -0.615766685385218282 -0.030807691817795201245
+0.016984136843969918629 0.010701026081884959518 -0.00083320727407271925197
+Earth 8.9970113821660187435e-10 0.010044870735102664462
 4.25875607065040958e-05
-0.75635861236241797023 -0.674672320414933413 2.9482164814591560215e-05
-0.0111724732704936106226 0.0127745538308708106445 -6.4922715710692383536e-07
-4 9.549535102761465607e-11 0.007246661019460395855
+1.0001792791661539006 0.06668748161964906107 -6.9475367832576531254e-06
+-0.0014241429939451050266 0.01710181935138167103 -8.172724609833309663e-07
+Mars 9.549535102761465607e-11 0.0072464333631564068194
 2.265740805092889601e-05
--1.6298746849997449715 0.3207423054955682029 0.04670239471945906301
--0.0021807443711779391643 -0.012535287802970449672 -0.00020920945169970240392
-5 2.825345908631354893e-07 0.3552709189640263194
+-1.6139182001611360739 -0.2770999554367851725 0.033781809741611629194
+0.0028882147021094439938 -0.01259648691593238945 -0.00033483851552870507427
+Jupiter 2.825345908631354893e-07 0.3552700143333522151
 0.00046732617030490929307
-4.173466317007961557 -2.8016935252076420326 -0.081737437087388009616
-0.0041198995131368296857 0.0066275220486694394126 -0.000119701756809504006665
-6 8.459715183006415395e-08 0.43765971211410006393
+4.3561675102222698897 -2.483239946173660062 -0.0871477099729481286
+0.0036506744364301680662 0.006918211883976329267 -0.00011041076017508120262
+Saturn 8.459715183006415395e-08 0.4376659280804963441
 0.00038925687730393611812
-6.414531809550852337 -7.603234575912382276 -0.12309230194363039723
-0.0039583234912346160553 0.003591394820962775982 -0.00021992254044702681153
-7 1.2920249163736673626e-08 0.4696151691794380732
+6.598405456116825718 -7.431912424938192707 -0.13338632598447389133
+0.0038655905358352319993 0.0036985431667748399145 -0.00021809450985937309415
+Uranus 1.2920249163736673626e-08 0.4697589307107089155
 0.00016953449859497231466
-14.779979482167510341 13.088063528768900667 -0.14289732557134240953
--0.0026326202792006140295 0.002767798188238951903 4.424098699891899271e-05
-8 1.5243589003230834323e-08 0.7813830605782720197
+14.6556082971347603205 13.217600500105490369 -0.14081174740381419141
+-0.0026597608840880260402 0.0027443623966001309648 4.4507838529215151932e-05
+Neptune 1.5243589003230834323e-08 0.78153946280858775143
 0.000164587904124493665
-29.57093474400743105 -4.53865809805519671 -0.5880859062837571205
-0.00046012900387533010914 0.0031291067120909890273 -7.4950441013985698475e-05
+29.592188021966471467 -4.391525979010755698 -0.5916011673528802639
+0.0004442402958062029259 0.0031318140342659721298 -7.463341927949002162e-05
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swifter.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swifter.in
index 1dbc75e21..de7157c2f 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swifter.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swifter.in
@@ -1,36 +1,36 @@
 9
-0 0.00029591220819207775568
+0 0.00029591220819207774
 0.0 0.0 0.0
 0.0 0.0 0.0
-1 4.9125474498983623693e-11 0.0014751244935834097723
+1 4.9125474498983623693e-11 0.0014751310862809727629
 1.6306381826061645943e-05
--0.37723213134178928962 0.033583006382262102496 0.037347605390151236704
--0.008342765357522348782 -0.026815373891535949219 -0.0014259978126226569104
-2 7.243452483873646905e-10 0.006759064884572926305
+0.3145650549772632254 -0.2555573396958932264 -0.04973776595957409008
+0.012185837286798669593 0.023148338651330341298 0.0007738432831418731988
+2 7.243452483873646905e-10 0.006759109593536554028
 4.0453784346544178454e-05
--0.48772324783973242113 -0.53438159383885197595 0.020810210727290629623
-0.014797158412775200664 -0.013730742274988789325 -0.0010423161661001279551
-3 8.9970113821660187435e-10 0.01004492566381686821
+0.387431535393453097 -0.615766685385218282 -0.030807691817795201245
+0.016984136843969918629 0.010701026081884959518 -0.00083320727407271925197
+3 8.9970113821660187435e-10 0.010044870735102664462
 4.25875607065040958e-05
-0.75635861236241797023 -0.674672320414933413 2.9482164814591560215e-05
-0.0111724732704936106226 0.0127745538308708106445 -6.4922715710692383536e-07
-4 9.549535102761465607e-11 0.007246661019460395855
+1.0001792791661539006 0.06668748161964906107 -6.9475367832576531254e-06
+-0.0014241429939451050266 0.01710181935138167103 -8.172724609833309663e-07
+4 9.549535102761465607e-11 0.0072464333631564068194
 2.265740805092889601e-05
--1.6298746849997449715 0.3207423054955682029 0.04670239471945906301
--0.0021807443711779391643 -0.012535287802970449672 -0.00020920945169970240392
-5 2.825345908631354893e-07 0.3552709189640263194
+-1.6139182001611360739 -0.2770999554367851725 0.033781809741611629194
+0.0028882147021094439938 -0.01259648691593238945 -0.00033483851552870507427
+5 2.825345908631354893e-07 0.3552700143333522151
 0.00046732617030490929307
-4.173466317007961557 -2.8016935252076420326 -0.081737437087388009616
-0.0041198995131368296857 0.0066275220486694394126 -0.000119701756809504006665
-6 8.459715183006415395e-08 0.43765971211410006393
+4.3561675102222698897 -2.483239946173660062 -0.0871477099729481286
+0.0036506744364301680662 0.006918211883976329267 -0.00011041076017508120262
+6 8.459715183006415395e-08 0.4376659280804963441
 0.00038925687730393611812
-6.414531809550852337 -7.603234575912382276 -0.12309230194363039723
-0.0039583234912346160553 0.003591394820962775982 -0.00021992254044702681153
-7 1.2920249163736673626e-08 0.4696151691794380732
+6.598405456116825718 -7.431912424938192707 -0.13338632598447389133
+0.0038655905358352319993 0.0036985431667748399145 -0.00021809450985937309415
+7 1.2920249163736673626e-08 0.4697589307107089155
 0.00016953449859497231466
-14.779979482167510341 13.088063528768900667 -0.14289732557134240953
--0.0026326202792006140295 0.002767798188238951903 4.424098699891899271e-05
-8 1.5243589003230834323e-08 0.7813830605782720197
+14.6556082971347603205 13.217600500105490369 -0.14081174740381419141
+-0.0026597608840880260402 0.0027443623966001309648 4.4507838529215151932e-05
+8 1.5243589003230834323e-08 0.78153946280858775143
 0.000164587904124493665
-29.57093474400743105 -4.53865809805519671 -0.5880859062837571205
-0.00046012900387533010914 0.0031291067120909890273 -7.4950441013985698475e-05
+29.592188021966471467 -4.391525979010755698 -0.5916011673528802639
+0.0004442402958062029259 0.0031318140342659721298 -7.463341927949002162e-05
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swiftest.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swiftest.in
index e506d4743..02e5eadf9 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swiftest.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/pl.swiftest.in
@@ -1,33 +1,33 @@
 8
-1 4.9125474498983623693e-11 0.0014751244935834097723
+Mercury 4.9125474498983623693e-11 0.0014751310862809727629
 1.6306381826061645943e-05
--0.37723213134178928962 0.033583006382262102496 0.037347605390151236704
--0.008342765357522348782 -0.026815373891535949219 -0.0014259978126226569104
-2 7.243452483873646905e-10 0.006759064884572926305
+0.3145650549772632254 -0.2555573396958932264 -0.04973776595957409008
+0.012185837286798669593 0.023148338651330341298 0.0007738432831418731988
+Venus 7.243452483873646905e-10 0.006759109593536554028
 4.0453784346544178454e-05
--0.48772324783973242113 -0.53438159383885197595 0.020810210727290629623
-0.014797158412775200664 -0.013730742274988789325 -0.0010423161661001279551
-3 8.9970113821660187435e-10 0.01004492566381686821
+0.387431535393453097 -0.615766685385218282 -0.030807691817795201245
+0.016984136843969918629 0.010701026081884959518 -0.00083320727407271925197
+Earth 8.9970113821660187435e-10 0.010044870735102664462
 4.25875607065040958e-05
-0.75635861236241797023 -0.674672320414933413 2.9482164814591560215e-05
-0.0111724732704936106226 0.0127745538308708106445 -6.4922715710692383536e-07
-4 9.549535102761465607e-11 0.007246661019460395855
+1.0001792791661539006 0.06668748161964906107 -6.9475367832576531254e-06
+-0.0014241429939451050266 0.01710181935138167103 -8.172724609833309663e-07
+Mars 9.549535102761465607e-11 0.0072464333631564068194
 2.265740805092889601e-05
--1.6298746849997449715 0.3207423054955682029 0.04670239471945906301
--0.0021807443711779391643 -0.012535287802970449672 -0.00020920945169970240392
-5 2.825345908631354893e-07 0.3552709189640263194
+-1.6139182001611360739 -0.2770999554367851725 0.033781809741611629194
+0.0028882147021094439938 -0.01259648691593238945 -0.00033483851552870507427
+Jupiter 2.825345908631354893e-07 0.3552700143333522151
 0.00046732617030490929307
-4.173466317007961557 -2.8016935252076420326 -0.081737437087388009616
-0.0041198995131368296857 0.0066275220486694394126 -0.000119701756809504006665
-6 8.459715183006415395e-08 0.43765971211410006393
+4.3561675102222698897 -2.483239946173660062 -0.0871477099729481286
+0.0036506744364301680662 0.006918211883976329267 -0.00011041076017508120262
+Saturn 8.459715183006415395e-08 0.4376659280804963441
 0.00038925687730393611812
-6.414531809550852337 -7.603234575912382276 -0.12309230194363039723
-0.0039583234912346160553 0.003591394820962775982 -0.00021992254044702681153
-7 1.2920249163736673626e-08 0.4696151691794380732
+6.598405456116825718 -7.431912424938192707 -0.13338632598447389133
+0.0038655905358352319993 0.0036985431667748399145 -0.00021809450985937309415
+Uranus 1.2920249163736673626e-08 0.4697589307107089155
 0.00016953449859497231466
-14.779979482167510341 13.088063528768900667 -0.14289732557134240953
--0.0026326202792006140295 0.002767798188238951903 4.424098699891899271e-05
-8 1.5243589003230834323e-08 0.7813830605782720197
+14.6556082971347603205 13.217600500105490369 -0.14081174740381419141
+-0.0026597608840880260402 0.0027443623966001309648 4.4507838529215151932e-05
+Neptune 1.5243589003230834323e-08 0.78153946280858775143
 0.000164587904124493665
-29.57093474400743105 -4.53865809805519671 -0.5880859062837571205
-0.00046012900387533010914 0.0031291067120909890273 -7.4950441013985698475e-05
+29.592188021966471467 -4.391525979010755698 -0.5916011673528802639
+0.0004442402958062029259 0.0031318140342659721298 -7.463341927949002162e-05
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
index 720db909b..fece80536 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/swiftest_rmvs_vs_swifter_rmvs.ipynb
@@ -21,9 +21,9 @@
      "output_type": "stream",
      "text": [
       "Reading Swifter file param.swifter.in\n",
-      "Reading in time 9.500e+03\n",
+      "Reading in time 3.652e+04\n",
       "Creating Dataset\n",
-      "Successfully converted 96 output frames.\n",
+      "Successfully converted 3653 output frames.\n",
       "Swifter simulation data stored as xarray DataSet .ds\n"
      ]
     }
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -45,9 +45,9 @@
      "output_type": "stream",
      "text": [
       "Reading Swiftest file param.swiftest.in\n",
-      "Reading in time 9.500e+03\n",
-      "Creating Dataset\n",
-      "Successfully converted 96 output frames.\n",
+      "\n",
+      "Creating Dataset from NetCDF file\n",
+      "Successfully converted 3653 output frames.\n",
       "Swiftest simulation data stored as xarray DataSet .ds\n"
      ]
     }
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -70,7 +70,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,32 +79,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "swiftdiff['rmag'] = np.sqrt(swiftdiff['px']**2 + swiftdiff['py']**2 + swiftdiff['pz']**2)\n",
-    "swiftdiff['vmag'] = np.sqrt(swiftdiff['vx']**2 + swiftdiff['vy']**2 + swiftdiff['vz']**2)"
+    "swiftdiff['rmag'] = np.sqrt(swiftdiff['xhx']**2 + swiftdiff['xhy']**2 + swiftdiff['xhz']**2)\n",
+    "swiftdiff['vmag'] = np.sqrt(swiftdiff['vhx']**2 + swiftdiff['vhy']**2 + swiftdiff['vhz']**2)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
-    "plidx = swiftdiff.id.values[swiftdiff.id.values < 10]\n",
-    "tpidx = swiftdiff.id.values[swiftdiff.id.values > 10]"
+    "plidx = swiftdiff.id.values[swiftdiff.id.values < 9]\n",
+    "tpidx = swiftdiff.id.values[swiftdiff.id.values >=9]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -125,12 +125,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -163,7 +163,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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U4BOSjit3sZldY2ZzzWxua2vJVQadc27EMjM6ch3F7VFZJTUA55CojjKzFeHP1cCtwBHDEJdzzg27Hz3zIw6/8XA2dW4CduCEIWkicDxwe2zfWEnjo+fAKcCzwxOhc84Nr3uW3gPAq1tf7bG/Fm0YtexWexNwAjBV0nLgS0AGwMyuDk97J3CvmbXFLt0FuDXsa9wA/NTM7q5V3M45V08yqQwAuUKu5u9ds4RhZudWcM51BN1v4/sWA4cMTVTOOTeyRY3dtRjAV1dVUs455ypTnBKkBlVREU8Yzjk3AkUli7zla/aenjCcc24ESVY9FaxQs/f2hOGccyNIVAUVlTA8YTjnnOtTlDg8YTjnnOtT1HbhbRjOOecAeG7dc/xm8W967Y9KFtHPWoz4rtk4DOeccwP3d7/+OwDetufbgO5Gby9hOOecq0ih0LOEUQueMJxzbgQpNnbjCcM551wFkm0YteAJwznnRpBiG0ahZxuGzyXlnHMO6F2S8BKGc865kqISRXE76iUV7q9Ft1pPGM45NwJkC1nAG72dc871I2c9F0yKutVGJY1obqmh5AnDOedGgGLVU2LgXi3bMjxhOOdcHXll8yusalvVa39yRHcyUYyqhCHpWkmrJT1b5vgJkjZJejJ8XBI7Nk/SQkmLJF1cq5idc67Wzv7V2Xzw7g/22p9cWS+ZKGoxRUgtSxjXAfP6OechM5sTPi4DkJQGvg+cChwAnCvpgCGN1Dnnhkl7rp1Xt77aa38yISTnkqrFUq01Sxhm9iCwfhCXHgEsMrPFZtYF3AycUdXgnHOuzvU3DmO0lTAqcbSkpyTdJenAcN90YFnsnOXhvpIkXSBpvqT5a9asGcpYnXOuZsq1YYzKEkYFngB2N7NDgO8Ct4X7S41GKXtnzOwaM5trZnNbW1urH6Vzzg2DZAkj2UtqhyphmNlmM9saPr8TyEiaSlCimBk7dQawYhhCdM65YZNMCMklWkdVL6n+SNpVYQdjSUcQxLYOeAzYR9IekhqBc4A7hi9S55yrvWigXmQ4xmHUbMU9STcBJwBTJS0HvgRkAMzsauBs4GOSckA7cI4FKTQn6ZPAPUAauNbMFtQqbuecqwf9tWGMqoRhZuf2c/x7wPfKHLsTuHMo4nLOuZGgvzaMHapKyjnnXHlRQojaLqKftSxheMJwzrkRoNzAvVqu7e0JwznnRoByA/eSI76HkicM55wbJmbGlY9dybNrS06x10OxREHpac29hOGcc6NYrpDjhr/dwLm/CfoE9TVaO9m4XWzDKPRMJEPJE4Zzzg2Tcl1l+zq3XHfa5DiNoeAJwznnhkm5domS5yYat3sljrCE8ZVHv8JJPz+p6rGCJwznnBs2yWVX+2q4TjZul1tAKVfI9THb3vbxhOGcc8MkWY3UZwmjTIIoVVWVSg3NV7snDOecGyZ9lTCSDeD9tmHEfqaVHpJ4PWE459ww6asNo78Fk/oqcaTkJQznnBtVoi6xxe1YCaPc3FHlShbxkd9ewnDOuVGmr2615Y4le0uVbMPwEoZzzo0uyaSQK3S3aRSsUDKBVFLSSKe8hOGcc6NKfyWMUlVUyalASpUwvErKOedGmf7aMHokkEJl4zAKVvAqKeecG+nMjF+88As6ch1A372k8pbvkVCSbRjlqqa8hOGcc6PAA8se4MuPfJmr/noV0Pc4jIIVemyXSxDReI14QhnxJQxJ10paLankPL6S3ivp6fDxJ0mHxI4tlfSMpCclza9VzM45V01bs1sBWNe+Digx0rvQswqq1LiM/towRsvAveuAeX0cXwIcb2YHA5cD1ySOn2hmc8xs7hDF55xzQyr6yz/60i+3ih70UcIo9D0OI2e5ISthNPR3gqRZFb7WRjPbXO6gmT0oaXYfx/8U23wUmFHh+zrn3IggBPRejzuSbMMoVcLolSDCrrjxqqnGVONQhN9/wgCuJ5j7UH2cYwQliBuqEBPA+cBdide/V5IBPzSzZOnDOefqnhQmjDKr5CUTRKlG7/5Geg/lOIx+E4aZnZjcJ2lXM1s1FAFJOpEgYbwptvsYM1shaWfgPknPm9mDZa6/ALgAYNasSgtHzjk39KKE0WMq8phkFVRy28x6t2EUupdqNbO6bPR+f1WjCEk6GPgRcIaZrYv2m9mK8Odq4FbgiHKvYWbXmNlcM5vb2to6FGE659ygKFFR02e32kLvgXulqqhKtXvUW6P3GZI+Kel11QokbCv5JXCemb0Q2z9W0vjoOXAK0P+K6c45V2eKjd5l2jCSJYq+Ekiymy0Eq+4N5cC9StowSnkX8AbgnZL2NrMP93eBpJuAE4CpkpYDXwIyAGZ2NXAJsBPwg7DYlgt7RO0C3BruawB+amZ3DzJu55wbNlEJI1mdFOmvDaPUehm1LGEMKmGY2WvA3eGj0mvO7ef4h4FeicfMFgOH9L7COedGlighRG0ZA+1WG08gyW620fO6m61W0vclXRc+P6WqETnn3CgVfclHJY1e3WoLfXerLTUZYcEK3d11sbocuNcFLA6fv7lKsTjn3KjWq1dUP5MPVjKQL2c5GtONxX35Qv1Nb74NmCgpA3jfVeecq0BfVVDQ/+SD8ePFNoxCnkwqU9xXj7PVrgdeAr4PPFy9cJxzbvR4dOWjnH7r6cXZaaMEMNg2jHgJJaqyMqyYMKKxG3VRJSVpkqT/Bc4Kd90A+NxOzjlXwjfmf4Olm5fy0qaXgL5LFMntUm0Y5do0ooQR7auLbrVmtlHS14HZwFrgYIKxE8455xKKf/kXes77FOmzhFEokFffvaSiBJJJdyeMoWz0Hky32vOBJWZ2D/B4leNxzrlRp+zstH2Mw8hbnpSlehyLr59hZsXr67KEEdoAfDQc5f0U8KSZ/bW6YTnn3MjXa3baPnpFJbcLVuizm218rqmGVEOPa4Zt8sEkM/uapN8CLwBzgOMATxjOOZcUTh0VlTCiEkJxHEYygSSqnGTdc08VrFCs0sqkMj1GgvfoVltPI70lXQakgScJShcPVDkm55wbVaIv+r6qoJLbyUbu+Ap8xYSRaPSOutXWTcIws0sk7UIwl9RZkvYys49UPzTnnBvZopJEMWEkqqCSa3rHt3OW61XCKCaIdOmEkbf88K64V8Y/Eixk5JMAOudcP6KEEf1MLn4EPRuxIewlRen1MTKpTI82jWKVVFgKqbeEcS3wsXC68RvN7MnqheScc6NDuRJGVJJItlkkB+ole0kV2yxSjeQKueLrNqWbiq9bsKFr9B5sGvoUQbJpAK6qXjjOOTd6RCO6kwmi+DM5srvMdOZppXuWMNI9SxhRwujKdwHU3dQgLwHNwO1mdlwV43HOuVEnmSBKrZaXK+TKTg3SmG7stR21V0B3woimIInaNKptsAljAfA74HxJj1UxHuecG3WiL/ZiW4b1bgTva/2LhlRDj+3mdDO5Qq44TqOYMPJBwmjQYFsb+jbYV90XWANcQzCQzznndnjRl370F35yvEVy0aNkG0Z86pD4OhfJbrSN6cYeJZKmhiBhtOfage6BfNU22BLGfgSD9T4HXFC9cJxzbuT69O8+zaE/PrTX/uT626V6SfU1kjvqFZUsYRQTRqJKqt4SxiTgC8BFQEclF0i6VtJqSc+WOS5JV0laJOlpSYfGjs2TtDA8dvEgY3bOuSH1wPIHSu5PdqstVyWVLGH0aMMoFHp0o81Z715S9ZowLiNo8F4IFPo7OXQdMK+P46cC+4SPC4D/ApCUJlh341TgAOBcSQcMLmznnKu9ZAmjVJVUstG71MjuZCN31CuqVxvGcCYMSWlJKyV9GMDMlpvZ/eHziv7iN7MHCRZeKucM4AYLPApMkrQbcASwyMwWm1kXcHN4rnPO1aXklB/JBFGql1TJbrWFnlVSyYF6yYSxLbcNGOaEYWZ54FlgryGJIjAdWBbbXh7uK7ffOefqUnLOqLID9xIlirzliz2c4m0YUbfa6HWa080AdOY7g+2GYHuoq6QG8qpjgIsknQysCPeZmVXrr32V2Gd97C/9ItIFhA3xs2b5cuPOudrLFrLFRY2gd7faqDtsqUbuTDpDLpcrLr8KsUbvRK+oKGFEJY6hHocxkIRxdPjz0PABfXxxD8JyYGZsewZBYmoss78kM7uGoLsvc+fOrWZ8zjlXkXILJSXbMno1chfyNKYbac+1B1ODhJVAmVSGbC7ba2R31I22paEF6G7DqIeEsceQRNDtDuCTkm4GjgQ2mdlKSWuAfSTtAbwKnAP8/RDH4pxzgxYliORKe8mlWuMljJwFjd6Nqe61LaKFlzLpDPlsvlevqKjNIkoYxXEYwz1wz8xe3p43knQTcAIwVdJy4EtAJnztq4E7gdOARcA24EPhsZykTwL3EKzDca2ZLdieWJxzbigl2yiS3WnLNXrnCjnSqTQppcgX8piChNGghh7rYyS70RZLGHXUhrFdzOzcfo4b8Ikyx+4kSCjOOVf3kgsm9SphlJmtNlr8KKVUsQ2jQQ1BAom3YZSrkhotCcM553YU5cZdJBNJfMGkfCGYTLAh1UBa6eL63Jl0JphLqpAnm88Cvaugkm0YdTNwT9LpQxGIc86NFskEkayiiqqWSjV6p5QqliiiBJJJZ8gWsmQLpRNG1M22Hkd6X1H1KJxzbhQp24aRSCDxhBGN9E4rXSxhZPNZMqlM0EuqRMKIEkRjupG00nU5+WCpcRHOOedC5RZKSrZd5Aq54oy00dxRDakG0qk0uUKObCEblDBSGbL5LLlCjgY1FLvNRgkikwqqrepipHeCj21wzrk+JEd2l+tOm7NcsQE7mo02rXSxRJEr5IoljK5CV3FAYLQEazFhhO0c27JBwoiqqKptaNbxc865HViyKqpcL6lcIVcctR31gkqn0j2qoKKEES9xRCWI+LiLTCrD1uxWoLsXVbV5wnDOuSrrNXdUog0jXuJoSgVf7lGjd7KEUWz0zmeLbRpRwujId5BSinQqXZxPCuorYbxW9Sicc24U6TWNeaINw7DiQL1oHqh4o3e0ol5UwmhMBetfdOY7eySM9lx7sT0jXg1VNwnDzE4eikCcc260KNcbKt4rKqqCikoG0RKtxSqpfLbYZhFNZBgliChJbMtu604Y4euklKqrRm/nnHMJ0bxPUKKXVKLRG7qnAolKBvESRY8qqVivqG25bWTSmeI1W7Nbi8kh2teUbkIams6snjCcc64K4vNC9SpZlFn/IlvI0pIJxlREjdyNqUYaUg3djd7p7iqoqEQRVTm1ZduKkxVGJYyoimsoDCphSPps7PnrqheOc86NTD2qm8rNIRWWGIDimtzRILxsPktXvqtYBZXsVgtBlVRDqqFHA3f0PF7CGCoDquiSNAn4FrCfpA7gaeB8wpllnXNuR5UsYZhZyTmlGtONwQJJhUKPhBGNs2hMNZJJZWjrauueGiRWJTWpaVLphNEw9AljQCUMM9toZh8CvgL8GTgW+OVQBOaccyNJqWk+4ttmRs5yxS/2aP2LqGRQ7Dabjk0FEk0Nku7ZyN2YaiyOEI+ur7uEEXM8QffaowDvNeWc2+HFE0ZUnRRJrs8N4ey0hRxjMmOK1/Rq9E6UMNqybTSmG5HUq2QRJY5xmXFD9hkHmzAmAV8ALgI6qhaNc86NUMkSRTRRIHQnB+guAUS9pIptGPGEkU6UMGJVUsm2imTiGN84fsg+42A7614G7GdmCyUV+j3bOedGoWwhS4MakNRjMaRcIdezisq6q6iiL/qo2qop3URKKbKFWKN3KkNXvgsz65EwoHfVU/RzbGZsj+NDYVAJw8yWA8vD5xdXNSLnnBshPnzPh2luaOaHJ/+wV5VUvIQRTyDRF3xnvhOgeyqQfLZHo3e2kMXMaEg19OgqGyWEqGQS/WxtaQWgK981VB93cAlD0veBsWb2QUmnmNm9VY7LOefq3hOrnyg+j6+elyxhRKO4IbYed2x1vEwqQ3uuHcN6tGFEvaqipAC9u89G25ObJwOw85idq/45I4Ntw+gCFofP31zpRZLmSVooaZGkXiUTSZ+X9GT4eFZSXtKU8NhSSc+Ex+YPMm7nnBsS8SqpXo3esTaMqJE7vthRJpUprmVR7CWVz9KR76CloYUxDWOKrxXNbhuVNKKqqKN2O4r3H/B+zn/9+UP1EQfdhrENmCgpA8yq5AJJaeD7BL2qlgOPSbrDzP4WnWNmVwJXhuefDnzGzNbHXuZEM1s7yJidc27IJEsYUZVUY6qxuNwqdFchRWtXRLPRRtuNqUYy6UyxBNKcbi6OBgdoSQfPo3aNiU0TgSARff7wzw/Z54PBlzDWAy8RJICHK7zmCGCRmS02sy7gZuCMPs4/F7hpkPE551xNlWv0bmpoChq4w+NRaaFYogiroNqybcXt+MyzzQ3NPUoYUckirWARpUlNk4boE/U2oIQhaZKk/wXOCnfdAMyt8PLpwLLY9vJwX6n3GQPMA26J7TbgXkmPS7qgjxgvkDRf0vw1a9ZUGJpzzm2fco3cLemWHm0YUZXUlq4tQHfCiFdJRdVMECaMTKxKKrZCH9RxwjCzjcDXgS8TjPTeh8pHepeaPrHccq+nAw8nqqOOMbNDgVOBT0g6rkyM15jZXDOb29raWmFozjm3fcqNw4hKGMkqqfjqeJl0zxJGPEE0p5uLEwxC9ziLC+deyEE7HcTcXSv9m337DaYN43xgiZndAzw+gOuWAzNj2zOAFWXOPYdEdZSZrQh/rpZ0K0EV14MDeH/nnKuaeBVUcjverba5oZmNHRvJ5oPtqPQQlTCa0k1kUhk2dmwEuhu9I80NzT2mK4/aLA6aehA3vb22tfaDacPYAHxU0rclfUjSGyq87jFgH0l7SGokSAp3JE+SNJFg6pHbY/vGShofPQdOAZ4dROzOOVcV8UZu6D2XVJQwWtIt5CxHVyEYHxFN3REljMZ0MO5iSzZMIKmmXiWMuChhDIcBlzDM7GuSfgu8AMwBjgP+WsF1OUmfBO4B0sC1ZrZA0kfD41eHp74TuNfM2mKX7wLcGmbZBuCnZnb3QGN3zrlqiUoMkR69pKxno3e+kC8O1BvXGCSMqAqqKd1ES0NLMYG0ZFqKDdrQe+T2lKYpVf4klRtwwpB0GcEX/pPAk2b2QKXXmtmdwJ2JfVcntq8DrkvsWwwcMtBYnXNuqCTniirXS6o53RyUMMIR2OMzQRvE1q6gDaMx3dijF1RLQ0uPJVajEsl5B5zHXUvuYtq4aUP0ifo3mDW9LwE6w2vPkvTfVY/KOefqXDxhRDPLFrfz3W0YYzNjKVih2AsqKmEUq6DSPaugkgP1oiqoCw+7kHvOuod0qrv0UWuDHYdxLbA/sBPwg+qF45xzI0MyYUQlDKEeVVLJRu6oxBCVMJrSTb1KGPFutVHCSKfSQ7r8aiUGmzA+RVCd1QB8p3rhOOfcyBBvw+jKd/XoFRXvJdUrYYQljKhbbWO6sVcJY0pzdztFPJkMt8EmjJeAZuB2Mys5HsI550azZAkjaqMYmxnbow0j2SuqKd1EQ6qhRy+peFIY0zCm2IbR0tDSo0vtcBvsXFILCEZtny/pSjM7vIoxOedc3euVMMJus2MaxvRIGMmR3U3pJhpTjT22e3SjDXtF3X7m7T16S9WDwSaMvQjGY1wT/nTOuR1KuRLGmMyYHlVSUQljc9dmIEgQzQ3NxUbwMZkxPaYvTymo+Nlz4p5D/yEGaLBVUsvM7A5gEfBcFeNxzrkRId6GEe8VFZUwonEXUaN1fO6oKIlEiyUN5Trc1TTYhDFP0gzgauBbVYzHOedGhKgKCnqWMFoyLeQKOTpyHQh1d6Pt2kJjqhGpe1/UID6Uix5V02ATxiTgC8BFBGMynHNuh5JckrUr31VcDClbyNKR6wiqn8KpPbZ0bSnONBuVKKK2ixnjZwCw35T9avkRBmywbRiXAfuZ2UJJ+X7Pds65USa+dnZXvouuQheNqUaa08105bvoyHfQ3NBcTBKbuzaTSQeTCkYJIyph7DJmF/7tyH/j8F3ru/9QRSUMSWlJKyV9GMDMlpvZ/eHzXkutOufcaJds9M7mszSmG2luaKYj30FnvpOmdFMxYWzs2FjsPpuskpLEOfudw16T9qrxpxiYihKGmeUJZoet70/jnHM1Ei9hRI3eUQmjI9dBZ64zKGGEa3DnLFdMENHPiY3DN/PsYAykSmoMcJGkk+lex8LMrK9lVp1zblSKlzC6Cl105bvIpDO0NLTQkeugI9/Ro4QB3YliQuMEACY3T65t0NtpIAnj6PDnoeEDyq+Y55xzo1qPEkY4cC9eJdWR66A53VxcIQ+6E8auY3cFGPa5oQZqIAljjyGLwjnnRpgebRj5oJdUY6qxOFJ7U9cmxmbGFksZnfnOYsI4YeYJ3P/y/Zx3wHnDEvtg9ZswJM0Kn5YsTcSObzSzzdUKzDnn6s2Gjg2MbxxPQ6qh5NQgjenGYjfaTZ2bipMIjm8cT2d7d8KY2jKVq0++uvcb1LlKShjXEySLvmbAMoJFj26oQkzOOVd38oU8x/3fcbxjr3dwxZuu6FUllc1nyaQyxWk+NnZuLCaPcZlxrG1f26N6aiTqN2GY2Ym1CMQ55+pZR74DgDteuoMr3nRFryqpznwnYxrGFKuk2rJtxYF50YyzU1um1jjq6hrsSO9BkTRP0kJJiyT1Gr8h6QRJmyQ9GT4uqfRa55wbSu259h7b0chuCEoY7bl2WhpaiqUKoFiiyKSCAXutLa01inZo1CxhSEoD3wdOBQ4AzpV0QIlTHzKzOeHjsgFe65xzQ6Ij19FjO1vIFgfidRW62JbdFsw8m+meeTZKGKfsfgoAB049sEbRDo1aljCOABaZ2WIz6wJuBiodw7E91zrn3HZLJoyufNDI3ZBqIJvPsi23jZaGlh6D8cZngoRx/uvP5/Yzb2f3CbvXNOZqq2XCmE6w6FJkebgv6WhJT0m6S1KUjiu9FkkXSJovaf6aNWuqEbdzzhWnK49EI7sbU43FKqkxDWN6DMaLShgNqYa6XN9ioGqZMEr1skp21X0C2N3MDgG+C9w2gGuDnWbXmNlcM5vb2jqy6wudc/Uj2YaRzWfJpDM0pZtoz7UHbRiZluL6FwATmibUOswhVcuEsRyYGdueQfcUIwCY2WYz2xo+vxPISJpaybXOOTeUol5Ska5CF5lUhjGZMaxrXwcEiyfFV8+LRnSPFrVMGI8B+0jaQ1IjcA5wR/wESbsq7H8m6YgwvnWVXOucc0Mp2YbRkeugpaGlOMYC6JEsAKaPLVlzPmINdj2MATOznKRPAvcAaeBaM1sg6aPh8auBs4GPScoB7cA5ZmZAyWtrFbtzziWrpNpz7TQ3NJNJZVjZthLoThhXHn8lC9YuYFLzpFqHOaRqljCgWM10Z2Lf1bHn3wO+V+m1zjlXK8kqqfZcO61jWjEz1mwLOthEA/XmzZ7HvNnzah7jUKtpwnDOuZGqM9ezl1Q0UC9FipwFy7WOtPUtBsoThnPOVaBUCaOloYW00sV9o60KKskThnPOVSDe6B2Nu2hON/dYIGlS06RhiKx2PGE451wF4gmjI9dRHHcRrZ4Hoz9h1HTyQeecG6niVVJt2TayhSwtDS1MGzutuH+kraA3UJ4wnHOuAvGpQTZ2bgSgJd3CtHHTylwx+niVlHPOVSDeS2p9x3ogGHex/077s+/kfTl3v3OHK7Sa8YThnHMVaM93D9yLRnaPbxxPU7qJW95xy3CFVVNeJeWccxWIlzBWb1sNjL7JBfvjCcM55yrQme8sTv3xWttrwOgfqJfkCcM55yrQnmtnclOw1sWqtlWAlzCcc86V0JnvZJexuwDwypZXAHqMwdgReMJwzrkKtGXbil1ol25eCnSvqLej8IThnHMV2JrdyuSmyYzPjKdgBSY3TaYhtWN1NPWE4Zxz/ShYgbZsG+MaxxXX7B5tq+lVwhOGc871oy3bBsC4zDimNE8BKLZn7Eg8YTjnXAnLNi/j9de/noeWP8TWrq1AkDBmTZgFwF4T9xrO8IaFJwznnCvh6bVPA3DbotvYkt0CwLjGccybPY8xDWN486w3D2d4w6KmCUPSPEkLJS2SdHGJ4++V9HT4+JOkQ2LHlkp6RtKTkubXMm7n3I4nnQoWRsoVcsUSxvjMeI6dcSyP/P0jHNx6cI/z712wihUb23u9zmhSsyZ+SWng+8DJwHLgMUl3mNnfYqctAY43sw2STgWuAY6MHT/RzNbWKmbn3I4rShKS2NS5CegeqJdS99/aG7d1ceJ/PsCGbVkAjtpzCt8991Baxzcx2tSyhHEEsMjMFptZF3AzcEb8BDP7k5ltCDcfBWbUMD7nnCuKpjAHWNexDoCdmnfqcc6Gti7mXHZfMVkAPLp4PYdfcT8/emgxbZ25msRaK7VMGNOBZbHt5eG+cs4H7optG3CvpMclXVDuIkkXSJovaf6aNWu2K2Dn3I4rKlV05DtY1x4kjCktU4rHn1m+iTdcfl/Z67/ym+c48Ev38Msnlg9toDVUy4ShEvus5InSiQQJ4wux3ceY2aHAqcAnJB1X6lozu8bM5prZ3NbW1u2N2Tm3g4oSxqaOTazvWM/4zPji+t23P/kqp3/vjxW9zmd/9hSzL/4NC1dtGbJYa6WWCWM5MDO2PQNYkTxJ0sHAj4AzzGxdtN/MVoQ/VwO3ElRxOefckIiqpDZ2bmRdxzqmtEwhly/wzfte4NM3Pzng13vrtx9kzmX3srkj2//JdaqWCeMxYB9Je0hqBM4B7oifIGkW8EvgPDN7IbZ/rKTx0XPgFODZmkXunNvhFEsYXZt4dcur7DpmN+Zcdh9X/fbFQb/mxm1ZDr70Xhas2FStMGuqZgnDzHLAJ4F7gOeAn5nZAkkflfTR8LRLgJ2AHyS6z+4C/FHSU8BfgN+Y2d21it05t+OJShhburawZPNSHnrO2FqlRuy3XfVH7lmwqiqvVUsyK9mMMCrMnTvX5s/3IRvOuYE77ubj2Ni5EQubWjteO5Xs+uPLnv+VMw/imgcX88r6bRW/x2fesi+fOmlvpFJNvMND0uNmNrfUMR/p7ZxzCblCjo2dGzl46qHFfYXOaSXPffdhM1j4lXm876jdefCiE/n9507gTXtPreh9vnX/C3xqEO0hw2XHmpvXOecqEJUs/vK3qTTtHOzLt8/qdd5tnziGOTMn9di3x9Sx/OTDR7K5I8tP//wKX7/r+T7f61dPreCVdW3c8rE30pCu77/hvUrKOTci5NasIb9lC5hhuTyWy5JqGUPjjOmQyVS1Wmfh+oWc/auzaV/+XgCs0ES+bd/i8b8/chaXvePAir7gzYzfPb+a86/v/7vo6UtPYUJzZvCBV0FfVVJewnDO1a3chg10PPssq//zG3QuXNjnuQ277MKEefNo2ndfxr7xaBpaW1HD4L7inlkZDLaz3Djy7Xv0OHbfZ45jn10qX2lPEiftvwtLv/42nl+1mXnffqjsuQdfei9PXXIKE8cMb9Iox0sYzrm6tO5/rmX1lVdu12uMPfZYGmfPJrPrLjS//vVkpk0nPWkS6XFjy16zeksHx3z/qzTvditbX7wYy00C4P1H786X33HgdpdkcvkCH7/xCe7922tlz7n/s8ez987jtut9BquvEoYnDOdc3Sm0tbHwsJLfWVUz4R2nM/7Nb6b5gANomDqV1JgxALz+0nvoHP8rGnf6I1ufvxxI8dBFJzJzypiqvv+zr27i7d8tP1r8txcez16ttU8aXiXlnBsxzIzN95Wfo6laNt/xKzbf8avidsucOTw5ew4t26Zhk9Zh2UlAikf+5c3sNrGl6u9/0PSJLPnaaXz65ie546lek15w0jf+MODqr6HmJQznXF3Z8LOfseqSLw13GDy89wTedMYn2POU48lMnz7o9pBKLFixibddVbq08bsLj2fPGpY0vErKOTcimBmrv/511l9/w3CH0kt60iQmnvUumvbep7tRPVW9brCbO7J85dd/42fze89u+6eL38y0SdUv5ZTiCcM5NyKsuuKrbPjxj4c7jIqNO/54JrztNJoPOICmvfeuymve8dQKPnXTX3vtv/+zx7H3zkNfPeUJwzk3Ijy33/7DHcJ2mfiudzHhtNNo2ncfMjvvPOjXeXldG8df+UCv/UPR+J7kU4M45+re+p/cONwhbLdNv/wlyz78YRYddzxL3vMe1l9/PR0LF5LfNLDZaXffaSzPXz6P10+f2GP/sf/xe17b3FHNkAfESxjOuWFlZrx2+eVs+OlN/Z6rpiZSE8ZDwbBclsKmzTWIsDrSO+3ExDPOYPxbTqL5da8jNbb8WJCImfHN+17gu79b1GP/g58/kVk7DU1Jw6uknHN1qevll3n1oovoeOrpksd3vvgLtBx0EI177kl64kSUTgNw+6Lb+eLDX+TB9zzI5ObJXHDPR5i/7BGOnngI3zr633n11YV89dZPMbtrAv+4/z+QX7uWzsVLyL32Grl168ivW1fy/WopPXEik9/3PsYceQRjDj+8zwGBpcZsPPC5E5g9tf+kM1CeMJxzdWfrH/7Asn/8aNnju15+GZPf/e6Sx0762Umsbl/NV9/0VU7b4zSOvflYtmS3MC4zjofPfZhfvPALLn/0cgCe+cAzAFzz9DW0trTyzn3eyUPPreSCH/2J8V3b+Mz+TZw2s4X8xk0sffZhlj7+APvmppJetbb6H7oPLYcdxqSzzqJlziE07blnr+NbOrIcf+UDrG/rKu579stvZVxTdbv7+sA951xd2frQH/tMFjOu/i/Gn3BCcfuRFY+wtn0tp+91Ol35LjZ3bS7u33PSnmzJbuGIXY/gL6v+wksbX+KRFY8Ur13VtorGdCPf/et3AThh+mmcd/0TZFqfYuy0lznnvOuKf91/6+GF3HPweB46534alaGwrR3LdpF95RU6Fy2i0N5BdvlyOhYsoHPJEvJrq5dU2h9/nPbHHwcgPXUqE976ViaeeSaZGdNpmDyZ8c0Znvh/J/Opm/5aHOj3uZ89xdXnHdbjdZZv2Ma2rjz7DsGAP08Yzrma6ly8mGUf+UjJY5ndZzHjqqtoft3rivtyhRwX3HcBAAdPPZjn1i6mI99BU2oM9y99iEde2gykeejRN9K4+2O8/boryUyaT6FzJumWZfxl1V/I5rvX0T7vx78AJtC8262sNXh+/fPsv9P+/Gbxb7ht0W2cvufpNKWbAMI5p8bSMHkyLYcc0iteMyO/di35rVvJvbaazhdeILf6NToWvkDHs8+S37BhUPcov3YtG268kQ03Bh0Bmg85mHHHHceEU0/lW2fuxxlzpnH+9fO5e8Eqnlq2kUPCKdYLBeOkb/yBzlyB5y+fR3MmPaj3L8erpJxzNZPfuJEXjjq61/6pH/8YE97+9mJVzNptm3hlbRfPr2znl8/fy0K+A0DX+jeSalxDqvlVOlaezZiZwQC/rg2H07nqLJqn30hmQlAF1bbkE7RMv5ldxo9nypgmVratZEvXVjrXvYlpTQezdtz3APjAAR/gwrkX8q473kVbto1bz7iVsZnqtA2YGYW2Nrpefhlrb6frlWV0LnyezqVL6Vq8hOyyZYN63XEnncQfp+zL5dumsy3TzOKvnkYqJf77h3/llafX8Ydd4cH/95ZBvXbdVElJmgd8B0gDPzKzryeOKzx+GrAN+KCZPVHJtc65+ta5ZAmLTz2tx74Z3/sum18/l7uXbOKu367kT9c8hxo2MGaP72LZKWxb9iHGzPo5Sk8gv202jVP+BEDHqtPJbz2A9hVnk2pcR9faE0gJdrfzaG78PbPGvo6V2/bnydUbWNP4U9Z0wicO+n9c9cgdNE55hMy4F2kttHLg1AO55cVbGN84nkUbF3HFm66oWrKAYGrz9LhxtBx4IABj5vb8HrZcDisUyK9ZQ8eLL9K1dCmdL77IxmdexF5cAKTYMHlfJm5aTDYzhjVT57DL6vnw298yh99yC7C2eRI3bFzAoW9/I11/7WJXUlzQMgEzq/rSrzUrYUhKAy8AJwPLgceAc83sb7FzTgP+iSBhHAl8x8yOrOTaUryE4WrBzMCsOE1E9H9KElYo9NhvBgYUis/DnxbuC88rGBAeL1i0zygUChQQjekULQ0pmhsE2SykUlg2S6FtG/mNG6GQh1QaCnmsq4tCRyeWz5HvytKxeSv5bdsoZLPBF1amkfzmzeS3bsWUorBhPQWDQr5AobMTy2ZRVydpM2jbgnI56OqChgbU2Ajt7eQKKQrZPNaVxRD5rjwF0mQLaXJqpGXuYWx4dQv5zVtpsA6e3/9kXmqZzPLOLLvmRVsK8uSYWTA2j3uJXOMGWttmsnbMq6QsxezOw5g4YzJbNqygpXMs+x04iy1r29m2Jcu0vSexYVUbua4CU2eO45UF6xg3uZkJU5tZ8PhrrCtsY31DJ9O7JrKpMQuTX2T8xlZ232cXxjCWBS+9yMsTnmMau3NQ0xx23XMiQuSyeXbZYwK5rgIAU2eMI583GjIpJkxtIdOUJpUWqbRKfjGbGflsgVy2wIaVbbRvyTJ2UhPrVmylfUsXE3ZqYekza8l1FZjY2sLLC9bRkEkxdlITS55ay8TWFpQSG1/bRnOLyGcLZHOiodDGzq/9kd2WP8yY9s0s2P99rJ2yF6ncZkhPYFLXUhp22o13XvZOGscPfDqRuuglJelo4FIze2u4/S8AZva12Dk/BB4ws5vC7YXACcDs/q4tZbAJ49vnvA+jMODrnHOuHogGPn3T9YMqYdRLldR0IF5ht5ygFNHfOdMrvBYASRcAFwDMmtV7Dd5KpNRI8Leec86NPFLpUs/2qmXCKBV98lu53DmVXBvsNLsGuAaCEsZAAox86qZrB3OZc86NarVMGMuBmbHtGUBy1ZBy5zRWcK1zzrkhVMvJBx8D9pG0h6RG4BzgjsQ5dwDvV+AoYJOZrazwWuecc0OoZiUMM8tJ+iRwD0HX2GvNbIGkj4bHrwbuJOghtYigW+2H+rq2VrE755zzgXvOOedifD0M55xz280ThnPOuYp4wnDOOVcRTxjOOecqMqobvSWtAV4e5OVTgdquoDJwIyFG8DiraSTECB5nNdU6xt3NrLXUgVGdMLaHpPnlegrUi5EQI3ic1TQSYgSPs5rqKUavknLOOVcRTxjOOecq4gmjvGuGO4AKjIQYweOsppEQI3ic1VQ3MXobhnPOuYp4CcM551xFPGE455yriCeMBEnzJC2UtEjSxcMUw1JJz0h6UtL8cN8USfdJejH8OTl2/r+E8S6U9NbY/sPC11kk6SptxxJckq6VtFrSs7F9VYtJUpOk/wv3/1nS7CrGeamkV8P7+WS4dvywxSlppqTfS3pO0gJJnw7319X97CPOerufzZL+IumpMM4v19v97CPGurqX/QoWpvdH2JaTBl4C9iRYtOkp4IBhiGMpMDWx7z+Ai8PnFwP/Hj4/IIyzCdgjjD8dHvsLcDTBioV3AaduR0zHAYcCzw5FTMDHgavD5+cA/1fFOC8FPlfi3GGJE9gNODR8Ph54IYylru5nH3HW2/0UMC58ngH+DBxVT/ezjxjr6l729/ASRk9HAIvMbLGZdQE3A2cMc0yRM4Drw+fXA2fG9t9sZp1mtoRgLZEjJO0GTDCzRyz4F3RD7JoBM7MHgfVDGFP8tX4BnBT95VSFOMsZljjNbKWZPRE+3wI8R7BufV3dzz7iLGe44jQz2xpuZsKHUUf3s48Yyxm2/0N98YTR03RgWWx7OX3/BxkqBtwr6XFJF4T7drFg9UHCnzuH+8vFPD18ntxfTdWMqXiNmeWATcBOVYz1k5KeVlBlFVVNDHucYbXBGwj+4qzb+5mIE+rsfkpKS3oSWA3cZ2Z1dz/LxAh1di/74gmjp1LZeDj6HR9jZocCpwKfkHRcH+eWi3k4P8tgYhrKeP8L2AuYA6wEvtHPe9YkTknjgFuAfzazzX2dWuY9hyvOurufZpY3sznADIK/xA/q4/RhibNMjHV3L/viCaOn5cDM2PYMYEWtgzCzFeHP1cCtBFVlr4XFUcKfq8PTy8W8PHye3F9N1YypeI2kBmAilVct9cnMXgv/sxaA/ya4n8Map6QMwZfwjWb2y3B33d3PUnHW4/2MmNlG4AFgHnV4P5Mx1vO9LMUTRk+PAftI2kNSI0HD0R21DEDSWEnjo+fAKcCzYRwfCE/7AHB7+PwO4Jywh8QewD7AX8Ii+BZJR4X1mO+PXVMt1Ywp/lpnA78L62i3W/SlEXonwf0ctjjD1/wf4Dkz+2bsUF3dz3Jx1uH9bJU0KXzeArwFeJ46up/lYqy3e9mvwbaWj9YHcBpBb5CXgH8bhvffk6B3xFPAgigGgrrI3wIvhj+nxK75tzDehcR6QgFzw3+ALwHfIxzZP8i4biIoMmcJ/pI5v5oxAc3Azwka9/4C7FnFOH8MPAM8TfCfarfhjBN4E0FVwdPAk+HjtHq7n33EWW/382Dgr2E8zwKXVPv/zPbG2UeMdXUv+3v41CDOOecq4lVSzjnnKuIJwznnXEU8YTjnnKuIJwznnHMV8YThnHOuIp4wnKuApEmSPh7bnibpF0P0XmdKuqTMsa3hz1ZJdw/F+ztXjicM5yoziWA2UCAYjW9mZw/Re10E/KCvE8xsDbBS0jFDFINzvXjCcK4yXwf2UrBmwZWSZitcc0PSByXdJulXkpZI+qSkz0r6q6RHJU0Jz9tL0t3hpJIPSdov+SaS9gU6zWxtuL2HpEckPSbp8sTptwHvHdJP7VyMJwznKnMx8JKZzTGzz5c4fhDw9wRzAV0BbDOzNwCPEEzfAHAN8E9mdhjwOUqXIo4Bnohtfwf4LzM7HFiVOHc+cOwgP49zA9Yw3AE4N0r83oI1I7ZI2gT8Ktz/DHBwOOPrG4Gfq3uJgqYSr7MbsCa2fQxwVvj8x8C/x46tBqZVJ3zn+ucJw7nq6Iw9L8S2CwT/z1LARgumt+5LO8Eso3Hl5u9pDs93ria8Ssq5ymwhWKZ0UCxYR2KJpHdDMBOspENKnPocsHds+2GCWZOhd3vFvnTPburckPOE4VwFzGwd8LCkZyVdOciXeS9wvqRoJuJSy/8+CLxB3fVWnyZYROsxepc8TgR+M8hYnBswn63WuToj6TvAr8zs/n7OexA4w8w21CYyt6PzEoZz9eerwJi+TpDUCnzTk4WrJS9hOOecq4iXMJxzzlXEE4ZzzrmKeMJwzjlXEU8YzjnnKuIJwznnXEX+P8xvwpP1S1dpAAAAAElFTkSuQmCC\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -186,7 +186,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -198,7 +198,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -230,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -590,64 +590,60 @@
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
        "Dimensions:  (id: 16)\n",
        "Coordinates:\n",
-       "  * id       (id) int64 101 102 103 104 105 106 107 ... 111 112 113 114 115 116\n",
-       "    time     float64 500.0\n",
+       "  * id       (id) int64 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n",
+       "    time     float64 50.0\n",
        "Data variables:\n",
+       "    xhx      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    xhy      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    xhz      (id) float64 0.0 0.0 0.0 0.0 -2.033e-20 ... 0.0 0.0 0.0 0.0 0.0\n",
+       "    vhx      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 3.469e-18 0.0\n",
+       "    vhy      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 2.168e-19 0.0\n",
+       "    vhz      (id) float64 0.0 0.0 0.0 0.0 -3.176e-22 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
        "    Gmass    (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
-       "    Radius   (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
-       "    px       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
-       "    py       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
-       "    pz       (id) float64 0.0 0.0 0.0 0.0 -1.775e-18 ... 0.0 -1.388e-17 0.0 0.0\n",
-       "    vx       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 -3.469e-18\n",
-       "    vy       (id) float64 0.0 0.0 0.0 0.0 ... -4.337e-19 2.168e-19 0.0\n",
-       "    vz       (id) float64 0.0 0.0 -1.084e-19 ... -4.066e-20 -1.355e-20\n",
-       "    rmag     (id) float64 0.0 0.0 0.0 0.0 1.775e-18 ... 0.0 1.388e-17 0.0 0.0\n",
-       "    vmag     (id) float64 0.0 0.0 1.084e-19 0.0 ... 4.4e-19 2.206e-19 3.469e-18</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b2a30202-5d0b-4727-9464-50be4065712e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b2a30202-5d0b-4727-9464-50be4065712e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>id</span>: 16</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-177f2f01-f8fe-4e0f-b87a-9896dd5c06eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-177f2f01-f8fe-4e0f-b87a-9896dd5c06eb' 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 class='xr-has-index'>id</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>101 102 103 104 ... 113 114 115 116</div><input id='attrs-99c4aa02-9de0-492a-bb15-fd1ab1e10c91' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99c4aa02-9de0-492a-bb15-fd1ab1e10c91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-633dfa96-74b6-46de-b990-f0b15b722e43' class='xr-var-data-in' type='checkbox'><label for='data-633dfa96-74b6-46de-b990-f0b15b722e43' 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([101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114,\n",
-       "       115, 116])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>500.0</div><input id='attrs-a4b0df95-5b22-45bb-a61f-cfe6125f233f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4b0df95-5b22-45bb-a61f-cfe6125f233f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-209a5d3d-eb94-477e-9449-ec4e181ae023' class='xr-var-data-in' type='checkbox'><label for='data-209a5d3d-eb94-477e-9449-ec4e181ae023' 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(500.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f58b4a8a-79fa-47d9-9026-5542f2190b5b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f58b4a8a-79fa-47d9-9026-5542f2190b5b' class='xr-section-summary' >Data variables: <span>(10)</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>Gmass</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-67a3308e-5f55-40c3-8c15-1cfbed30ff66' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67a3308e-5f55-40c3-8c15-1cfbed30ff66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a62a02a2-e94d-4664-aa21-7ec364b6a650' class='xr-var-data-in' type='checkbox'><label for='data-a62a02a2-e94d-4664-aa21-7ec364b6a650' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
-       "       nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radius</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-18266066-2a22-48b9-81e3-4886cd78eef2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-18266066-2a22-48b9-81e3-4886cd78eef2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1aefa1a-5546-4fd4-8d1a-674f7bdbd023' class='xr-var-data-in' type='checkbox'><label for='data-c1aefa1a-5546-4fd4-8d1a-674f7bdbd023' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
-       "       nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>px</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-d7565652-be1d-4344-8ce7-9f745629054c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7565652-be1d-4344-8ce7-9f745629054c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78f0b6b1-7ed7-4ea3-8843-3738f2f8802a' class='xr-var-data-in' type='checkbox'><label for='data-78f0b6b1-7ed7-4ea3-8843-3738f2f8802a' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
-       "       0.00000000e+00, 0.00000000e+00, 5.55111512e-17, 0.00000000e+00,\n",
-       "       0.00000000e+00, 8.88178420e-16, 0.00000000e+00, 0.00000000e+00,\n",
-       "       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>py</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-d3a4aed2-8feb-4bd2-9d02-273ce98a05a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3a4aed2-8feb-4bd2-9d02-273ce98a05a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-743c2b7a-fcbd-48c0-9ad5-97a1363760de' class='xr-var-data-in' type='checkbox'><label for='data-743c2b7a-fcbd-48c0-9ad5-97a1363760de' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pz</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... -1.388e-17 0.0 0.0</div><input id='attrs-245bde7d-7165-452c-9ce4-ab9994fc9798' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-245bde7d-7165-452c-9ce4-ab9994fc9798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-720ac776-557e-45e2-860f-ea3fdd9e10d6' class='xr-var-data-in' type='checkbox'><label for='data-720ac776-557e-45e2-860f-ea3fdd9e10d6' 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([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
-       "       -1.77538106e-18, -1.63985579e-18,  0.00000000e+00, -3.46944695e-18,\n",
-       "        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
-       "        0.00000000e+00, -1.38777878e-17,  0.00000000e+00,  0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vx</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.0 0.0 -3.469e-18</div><input id='attrs-6c66f8da-a7c9-4930-ba10-ffd23a2ee15a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c66f8da-a7c9-4930-ba10-ffd23a2ee15a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a8695af-9910-448b-a26c-9a0a70648f64' class='xr-var-data-in' type='checkbox'><label for='data-5a8695af-9910-448b-a26c-9a0a70648f64' 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([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
-       "        0.00000000e+00,  0.00000000e+00,  1.73472348e-18,  0.00000000e+00,\n",
-       "        0.00000000e+00,  8.67361738e-19,  0.00000000e+00,  0.00000000e+00,\n",
-       "        0.00000000e+00,  0.00000000e+00,  0.00000000e+00, -3.46944695e-18])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vy</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 2.168e-19 0.0</div><input id='attrs-6861f1a0-9ea5-44cc-87db-8a23c1bb4c67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6861f1a0-9ea5-44cc-87db-8a23c1bb4c67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6699883-9a9b-4769-9edd-7b6900b2d518' class='xr-var-data-in' type='checkbox'><label for='data-e6699883-9a9b-4769-9edd-7b6900b2d518' 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([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
-       "        0.00000000e+00,  0.00000000e+00, -3.25260652e-19,  0.00000000e+00,\n",
+       "    radius   (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
+       "    rmag     (id) float64 0.0 0.0 0.0 0.0 2.033e-20 ... 0.0 0.0 0.0 0.0 0.0\n",
+       "    vmag     (id) float64 0.0 0.0 0.0 0.0 3.176e-22 ... 0.0 0.0 3.476e-18 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-617c718e-ca7a-4cc3-8adc-ff7519224470' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-617c718e-ca7a-4cc3-8adc-ff7519224470' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>id</span>: 16</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8b5b0d1b-b2e3-4bcd-a4df-72b0c7dc029c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b5b0d1b-b2e3-4bcd-a4df-72b0c7dc029c' 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 class='xr-has-index'>id</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>9 10 11 12 13 14 ... 20 21 22 23 24</div><input id='attrs-943e217b-19bc-4c8f-a8b7-625d7ab6fb75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-943e217b-19bc-4c8f-a8b7-625d7ab6fb75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce76b17d-8bee-46e9-b38e-4b48fe96f29b' class='xr-var-data-in' type='checkbox'><label for='data-ce76b17d-8bee-46e9-b38e-4b48fe96f29b' 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'><dt><span>_FillValue :</span></dt><dd>-2147483647</dd></dl></div><div class='xr-var-data'><pre>array([ 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>50.0</div><input id='attrs-be1301da-8b3f-4db8-8c5a-a71c1502c473' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be1301da-8b3f-4db8-8c5a-a71c1502c473' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09ace323-947b-4d08-878e-05661e7d92de' class='xr-var-data-in' type='checkbox'><label for='data-09ace323-947b-4d08-878e-05661e7d92de' 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'><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array(50.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8e2b79e-7d9b-47af-aa91-19a8fee748f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8e2b79e-7d9b-47af-aa91-19a8fee748f3' class='xr-section-summary' >Data variables: <span>(10)</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>xhx</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-29f7a690-4c94-4e3a-8d99-c64f084606a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-29f7a690-4c94-4e3a-8d99-c64f084606a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44083907-34ce-4139-93a3-19f9ae2cb825' class='xr-var-data-in' type='checkbox'><label for='data-44083907-34ce-4139-93a3-19f9ae2cb825' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xhy</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-634c1410-e76c-48b0-a96f-49b950d56dc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-634c1410-e76c-48b0-a96f-49b950d56dc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4240d36-bd29-4641-9d40-f96a36290f6f' class='xr-var-data-in' type='checkbox'><label for='data-e4240d36-bd29-4641-9d40-f96a36290f6f' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xhz</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-d37e71b3-5e32-4a35-802d-0ff450cee802' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d37e71b3-5e32-4a35-802d-0ff450cee802' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-caa50bc4-b37a-4b1a-b793-b9a52a771cbe' class='xr-var-data-in' type='checkbox'><label for='data-caa50bc4-b37a-4b1a-b793-b9a52a771cbe' 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([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
+       "       -2.03287907e-20, -6.77626358e-21,  0.00000000e+00,  0.00000000e+00,\n",
        "        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
-       "       -2.16840434e-19, -4.33680869e-19,  2.16840434e-19,  0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vz</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 ... -4.066e-20 -1.355e-20</div><input id='attrs-86155d7a-b5c1-4433-9de0-05c14c3ff969' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86155d7a-b5c1-4433-9de0-05c14c3ff969' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fde1a1b4-941d-4bb7-88e6-04cef833f3e0' class='xr-var-data-in' type='checkbox'><label for='data-fde1a1b4-941d-4bb7-88e6-04cef833f3e0' 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([ 0.00000000e+00,  0.00000000e+00, -1.08420217e-19,  0.00000000e+00,\n",
-       "       -5.97687623e-20, -5.54806580e-20, -1.08420217e-19, -1.08420217e-19,\n",
-       "       -6.77626358e-20, -4.33680869e-19, -1.08420217e-19, -4.06575815e-20,\n",
-       "       -7.45388994e-20, -7.45388994e-20, -4.06575815e-20, -1.35525272e-20])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rmag</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 1.388e-17 0.0 0.0</div><input id='attrs-e90098c3-0d51-4715-bca8-04478326e239' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e90098c3-0d51-4715-bca8-04478326e239' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8f31483-04e6-42de-9b7e-c06744dedb9c' class='xr-var-data-in' type='checkbox'><label for='data-e8f31483-04e6-42de-9b7e-c06744dedb9c' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
-       "       1.77538106e-18, 1.63985579e-18, 5.55111512e-17, 3.46944695e-18,\n",
-       "       0.00000000e+00, 8.88178420e-16, 0.00000000e+00, 0.00000000e+00,\n",
-       "       0.00000000e+00, 1.38777878e-17, 0.00000000e+00, 0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vmag</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 ... 2.206e-19 3.469e-18</div><input id='attrs-acf26cd7-7d5d-4a35-b908-97d48cdeb1d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acf26cd7-7d5d-4a35-b908-97d48cdeb1d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d236ae62-2907-4ade-bb83-d45641c6f409' class='xr-var-data-in' type='checkbox'><label for='data-d236ae62-2907-4ade-bb83-d45641c6f409' 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([0.00000000e+00, 0.00000000e+00, 1.08420217e-19, 0.00000000e+00,\n",
-       "       5.97687623e-20, 5.54806580e-20, 1.76828023e-18, 1.08420217e-19,\n",
-       "       6.77626358e-20, 9.69739904e-19, 1.08420217e-19, 4.06575815e-20,\n",
-       "       2.29294181e-19, 4.40039934e-19, 2.20619158e-19, 3.46947342e-18])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3cea84b0-7e53-4a84-a3ad-d7b9774ff215' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3cea84b0-7e53-4a84-a3ad-d7b9774ff215' 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>"
+       "        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vhx</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.0 3.469e-18 0.0</div><input id='attrs-a2b34676-6679-4b50-a3f3-a55aa6d5334b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2b34676-6679-4b50-a3f3-a55aa6d5334b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97b29152-ebbb-4592-9d0b-862790f23e33' class='xr-var-data-in' type='checkbox'><label for='data-97b29152-ebbb-4592-9d0b-862790f23e33' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 6.93889390e-18, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 3.46944695e-18, 0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vhy</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.0 2.168e-19 0.0</div><input id='attrs-d21ec23e-acd6-42d9-9aae-625b87e31240' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d21ec23e-acd6-42d9-9aae-625b87e31240' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36218a64-f323-4708-91bf-55a95b60c18c' class='xr-var-data-in' type='checkbox'><label for='data-36218a64-f323-4708-91bf-55a95b60c18c' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 2.16840434e-19, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 2.16840434e-19, 0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vhz</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-a08fdee5-a380-422d-9182-6cac3bb0b48c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a08fdee5-a380-422d-9182-6cac3bb0b48c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0eb1004-28c1-4dc7-9a98-e48cf72b0930' class='xr-var-data-in' type='checkbox'><label for='data-a0eb1004-28c1-4dc7-9a98-e48cf72b0930' 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([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
+       "       -3.17637355e-22,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
+       "        1.35525272e-20,  0.00000000e+00,  2.71050543e-20,  0.00000000e+00,\n",
+       "        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Gmass</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fa2ca345-3e6e-4630-9cb0-3f90090498e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fa2ca345-3e6e-4630-9cb0-3f90090498e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53ed3c86-9614-441b-b6b3-52139c8c8bcf' class='xr-var-data-in' type='checkbox'><label for='data-53ed3c86-9614-441b-b6b3-52139c8c8bcf' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
+       "       nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radius</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea864370-50e9-4442-9dfa-ea2967b6a4be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea864370-50e9-4442-9dfa-ea2967b6a4be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52986d97-8122-40f1-8466-fadd2d461349' class='xr-var-data-in' type='checkbox'><label for='data-52986d97-8122-40f1-8466-fadd2d461349' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
+       "       nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rmag</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-dbfbad9b-6e2d-4d02-a5dc-1974465b1bf4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dbfbad9b-6e2d-4d02-a5dc-1974465b1bf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-484ade33-3674-45d5-930e-8016e26876ef' class='xr-var-data-in' type='checkbox'><label for='data-484ade33-3674-45d5-930e-8016e26876ef' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       2.03287907e-20, 6.77626358e-21, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vmag</span></div><div class='xr-var-dims'>(id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.0 3.476e-18 0.0</div><input id='attrs-f3255cb3-7cc8-4540-8646-3d58273fc96f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3255cb3-7cc8-4540-8646-3d58273fc96f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcc48d87-359e-4337-b28b-c6211d95242c' class='xr-var-data-in' type='checkbox'><label for='data-fcc48d87-359e-4337-b28b-c6211d95242c' 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([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       3.17637355e-22, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
+       "       1.35525272e-20, 6.93889390e-18, 2.18527934e-19, 0.00000000e+00,\n",
+       "       0.00000000e+00, 0.00000000e+00, 3.47621661e-18, 0.00000000e+00])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eef7c0be-8b37-4e6b-989a-7b6c3d205690' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eef7c0be-8b37-4e6b-989a-7b6c3d205690' 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>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
        "Dimensions:  (id: 16)\n",
        "Coordinates:\n",
-       "  * id       (id) int64 101 102 103 104 105 106 107 ... 111 112 113 114 115 116\n",
-       "    time     float64 500.0\n",
+       "  * id       (id) int64 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24\n",
+       "    time     float64 50.0\n",
        "Data variables:\n",
+       "    xhx      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    xhy      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    xhz      (id) float64 0.0 0.0 0.0 0.0 -2.033e-20 ... 0.0 0.0 0.0 0.0 0.0\n",
+       "    vhx      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 3.469e-18 0.0\n",
+       "    vhy      (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 2.168e-19 0.0\n",
+       "    vhz      (id) float64 0.0 0.0 0.0 0.0 -3.176e-22 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
        "    Gmass    (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
-       "    Radius   (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
-       "    px       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
-       "    py       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
-       "    pz       (id) float64 0.0 0.0 0.0 0.0 -1.775e-18 ... 0.0 -1.388e-17 0.0 0.0\n",
-       "    vx       (id) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 -3.469e-18\n",
-       "    vy       (id) float64 0.0 0.0 0.0 0.0 ... -4.337e-19 2.168e-19 0.0\n",
-       "    vz       (id) float64 0.0 0.0 -1.084e-19 ... -4.066e-20 -1.355e-20\n",
-       "    rmag     (id) float64 0.0 0.0 0.0 0.0 1.775e-18 ... 0.0 1.388e-17 0.0 0.0\n",
-       "    vmag     (id) float64 0.0 0.0 1.084e-19 0.0 ... 4.4e-19 2.206e-19 3.469e-18"
+       "    radius   (id) float64 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
+       "    rmag     (id) float64 0.0 0.0 0.0 0.0 2.033e-20 ... 0.0 0.0 0.0 0.0 0.0\n",
+       "    vmag     (id) float64 0.0 0.0 0.0 0.0 3.176e-22 ... 0.0 0.0 3.476e-18 0.0"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/tp.in b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/tp.in
index e8eeff31e..684c167b5 100644
--- a/examples/rmvs_swifter_comparison/8pl_16tp_encounters/tp.in
+++ b/examples/rmvs_swifter_comparison/8pl_16tp_encounters/tp.in
@@ -1,49 +1,49 @@
 16
-101
--0.37720907063545766613 0.033606067088593753744 0.037347605390151236704
--0.0057392158855131963913 -0.026815373891535949219 -0.0014259978126226569104
-102
--0.37725519204812091312 0.033559945675930451248 0.037347605390151236704
--0.010946314829531501173 -0.026815373891535949219 -0.0014259978126226569104
-103
--0.48766603754926024505 -0.53432438354837974437 0.020810210727290629623
-0.021144392118120594604 -0.013730742274988789325 -0.0010423161661001279551
-104
--0.4877804581302045972 -0.53443880412932420754 0.020810210727290629623
-0.008449924707429806725 -0.013730742274988789325 -0.0010423161661001279551
-105
-0.7564188402683574841 -0.6746120925089938991 2.9482164814591560215e-05
-0.018066913504767485171 0.0127745538308708106445 -6.4922715710692383536e-07
-106
-0.75629838445647845635 -0.67473254832087292687 2.9482164814591560215e-05
-0.0042780330362197352065 0.0127745538308708106445 -6.4922715710692383536e-07
-107
--1.6298426425859910971 0.3207743479093220218 0.04670239471945906301
-0.00089873472704595381427 -0.012535287802970449672 -0.00020920945169970240392
-108
--1.6299067274134988459 0.32071026308181438402 0.04670239471945906301
--0.005260223469401832143 -0.012535287802970449672 -0.00020920945169970240392
-109
-4.174127216016058739 -2.8010326261995448505 -0.081737437087388009616
-0.041002116714784257734 0.0066275220486694394126 -0.000119701756809504006665
-110
-4.1728054179998643747 -2.8023544242157392148 -0.081737437087388009616
--0.032762317688510601832 0.0066275220486694394126 -0.000119701756809504006665
-111
-6.415082301905982831 -7.602684083557251782 -0.12309230194363039723
-0.026071492374768204248 0.003591394820962775982 -0.00021992254044702681153
-112
-6.413981317195721843 -7.60378506826751277 -0.12309230194363039723
--0.018154845392298973872 0.003591394820962775982 -0.00021992254044702681153
-113
-14.780219240154712779 13.088303286756103105 -0.14289732557134240953
-0.010462143259461278988 0.002767798188238951903 4.424098699891899271e-05
-114
-14.779739724180307903 13.087823770781698229 -0.14289732557134240953
--0.015727383817862507914 0.002767798188238951903 4.424098699891899271e-05
-115
-29.571167506453647889 -4.538425335608981648 -0.5880859062837571205
-0.01489576481715346179 0.0031291067120909890273 -7.4950441013985698475e-05
-116
-29.570701981561214211 -4.5388908605014117725 -0.5880859062837571205
--0.013975506809402800379 0.0031291067120909890273 -7.4950441013985698475e-05
+9
+0.3145881156835948489 -0.2555342789895616029 -0.04973776595957409008
+0.014789386758807821984 0.023148338651330341298 0.0007738432831418731988
+10
+0.3145419942709316019 -0.2555804004022248499 -0.04973776595957409008
+0.009582287814789517202 0.023148338651330341298 0.0007738432831418731988
+11
+0.38748874568392527307 -0.6157094750947460504 -0.030807691817795201245
+0.023331370549315312568 0.010701026081884959518 -0.00083320727407271925197
+12
+0.38737432510298092092 -0.6158238956756905136 -0.030807691817795201245
+0.0106369031386245246895 0.010701026081884959518 -0.00083320727407271925197
+13
+1.0002395070720935255 0.06674770952558858883 -6.9475367832576531254e-06
+0.0054702972403287706063 0.01710181935138167103 -8.172724609833309663e-07
+14
+1.0001190512602142757 0.06662725371370953331 -6.9475367832576531254e-06
+-0.008318583228218981093 0.01710181935138167103 -8.172724609833309663e-07
+15
+-1.6138861577473821995 -0.2770679130230313536 0.033781809741611629194
+0.005967693800333337406 -0.01259648691593238945 -0.00033483851552870507427
+16
+-1.6139502425748899483 -0.27713199785053899138 0.033781809741611629194
+-0.00019126439611444898473 -0.01259648691593238945 -0.00033483851552870507427
+17
+4.356828409230367072 -2.48257904716556288 -0.0871477099729481286
+0.04053289163807759915 0.006918211883976329267 -0.00011041076017508120262
+18
+4.3555066112141727075 -2.4839008451817572443 -0.0871477099729481286
+-0.033231542765217260416 0.006918211883976329267 -0.00011041076017508120262
+19
+6.598955948471956212 -7.431361932583062213 -0.13338632598447389133
+0.025978759419368821493 0.0036985431667748399145 -0.00021809450985937309415
+20
+6.597854963761695224 -7.4324629172933232013 -0.13338632598447389133
+-0.018247578347698356627 0.0036985431667748399145 -0.00021809450985937309415
+21
+14.6558480551219627586 13.217840258092692807 -0.14081174740381419141
+0.010435002654573867845 0.0027443623966001309648 4.4507838529215151932e-05
+22
+14.6553685391475578825 13.217360742118287931 -0.14081174740381419141
+-0.015754524422749920792 0.0027443623966001309648 4.4507838529215151932e-05
+23
+29.592420784412688306 -4.3912932165645406357 -0.5916011673528802639
+0.014879876109084333793 0.0031318140342659721298 -7.463341927949002162e-05
+24
+29.591955259520254629 -4.3917587414569707605 -0.5916011673528802639
+-0.013991395517471928375 0.0031318140342659721298 -7.463341927949002162e-05
diff --git a/src/io/io.f90 b/src/io/io.f90
index 29562763b..2b0ba4468 100644
--- a/src/io/io.f90
+++ b/src/io/io.f90
@@ -73,7 +73,6 @@ module subroutine io_conservation_report(self, param, lterminal)
             if (abs(Merror) > 100 * epsilon(Merror)) then
                write(*,*) "Severe error! Mass not conserved! Halting!"
                call pl%xv2el(cb)
-               !call param%nciu%open(param)
                call self%write_hdr(param%nciu, param)
                call cb%write_frame(param%nciu, param)
                call pl%write_frame(param%nciu, param)
diff --git a/src/main/swiftest_driver.f90 b/src/main/swiftest_driver.f90
index 755468868..965c89d1d 100644
--- a/src/main/swiftest_driver.f90
+++ b/src/main/swiftest_driver.f90
@@ -88,9 +88,7 @@ program swiftest_driver
             iout = iout - 1
             if (iout == 0) then
                ioutput = ioutput_t0 + iloop / istep_out
-               call timer%finish(nsubsteps=istep_out, message="Integration steps:", param=param)
                if (t > old_t_final) call nbody_system%write_frame(param)
-               call timer%finish(nsubsteps=1,         message="File I/O:         ", param=param)
                iout = istep_out
             end if
          end if
@@ -99,6 +97,7 @@ program swiftest_driver
          if (istep_dump > 0) then
             idump = idump - 1
             if (idump == 0) then
+               call timer%finish(nsubsteps=istep_dump, message="Integration steps:", param=param)
                call nbody_system%dump(param)
                idump = istep_dump
             end if
@@ -106,8 +105,6 @@ program swiftest_driver
       end do
    end associate
 
-   call nbody_system%finalize(param)
-
    call util_exit(SUCCESS)
 
    stop
diff --git a/src/modules/walltime_classes.f90 b/src/modules/walltime_classes.f90
index a538baad8..1d1ac5142 100644
--- a/src/modules/walltime_classes.f90
+++ b/src/modules/walltime_classes.f90
@@ -15,11 +15,13 @@ module walltime_classes
       integer(I8B) :: count_max                  !! Maximum value of the clock ticker
       integer(I8B) :: count_start_main           !! Value of the clock ticker at when the timer is first called
       integer(I8B) :: count_start_step           !! Value of the clock ticker at the start of a timed step
-      integer(I8B) :: count_finish_step          !! Value of the clock ticker at the end of a timed step
+      integer(I8B) :: count_stop_step            !! Value of the clock ticker at the end of a timed step
+      real(DP)     :: wall_step                  !! Value of the step elapsed time
       logical      :: lmain_is_started = .false. !! Logical flag indicating whether or not the main timer has been reset or not
    contains
       procedure :: reset  => walltime_reset  !! Resets the clock ticker, settting main_start to the current ticker value
-      procedure :: start  => walltime_start  !! Starts the timer, setting step_start to the current ticker value
+      procedure :: start  => walltime_start  !! Starts the timer, setting count_start_step to the current ticker value
+      procedure :: stop   => walltime_stop   !! Stops the timer, setting count_stop_step to the current ticker value
       procedure :: finish => walltime_finish !! Ends the timer, setting step_finish to the current ticker value and printing the elapsed time information to the terminal
    end type walltimer
 
@@ -65,6 +67,13 @@ module subroutine walltime_start(self, param)
          class(walltimer),           intent(inout) :: self  !! Walltimer object
          class(swiftest_parameters), intent(inout) :: param !! Current run configuration parameters
       end subroutine walltime_start
+
+      module subroutine walltime_stop(self, param)
+         use swiftest_classes, only : swiftest_parameters
+         implicit none
+         class(walltimer),           intent(inout) :: self  !! Walltimer object
+         class(swiftest_parameters), intent(inout) :: param !! Current run configuration parameters
+      end subroutine walltime_stop
    end interface
 
    interface
diff --git a/src/walltime/walltime.f90 b/src/walltime/walltime.f90
index 2da539285..6f8897d98 100644
--- a/src/walltime/walltime.f90
+++ b/src/walltime/walltime.f90
@@ -15,7 +15,7 @@ module subroutine walltime_finish(self, nsubsteps, message, param)
       ! Internals
       character(len=*), parameter     :: walltimefmt = '" Wall time (s): ", es12.5, "; Wall time/step in this interval (s):  ", es12.5'
       character(len=STRMAX)           :: fmt
-      integer(I8B)                    :: count_delta_step, count_delta_main
+      integer(I8B)                    :: count_delta_step, count_delta_main, count_finish_step
       real(DP)                        :: wall_main         !! Value of total elapsed time at the end of a timed step
       real(DP)                        :: wall_step         !! Value of elapsed time since the start of a timed step
       real(DP)                        :: wall_per_substep  !! Value of time per substep 
@@ -25,13 +25,13 @@ module subroutine walltime_finish(self, nsubsteps, message, param)
          return
       end if
 
-      call system_clock(self%count_finish_step)
+      call self%stop(param)
+      count_finish_step = self%count_stop_step
 
-      count_delta_step = self%count_finish_step - self%count_start_step
-      count_delta_main = self%count_finish_step - self%count_start_main
-      wall_step = count_delta_step / (self%count_rate * 1.0_DP)
+      count_delta_step = count_finish_step - self%count_start_step
+      count_delta_main = count_finish_step - self%count_start_main
       wall_main = count_delta_main / (self%count_rate * 1.0_DP)
-      wall_per_substep = wall_step / nsubsteps
+      wall_per_substep = self%wall_step / nsubsteps
 
       fmt = '("' //  adjustl(message) // '",' // walltimefmt // ')'
       write(*,trim(adjustl(fmt))) wall_main, wall_per_substep
@@ -79,6 +79,31 @@ module subroutine walltime_start(self, param)
    end subroutine walltime_start
 
 
+   module subroutine walltime_stop(self, param)
+      !! author: David A. Minton
+      !!
+      !! Starts the timer, setting step_start to the current ticker value
+      implicit none
+      ! Arguments
+      class(walltimer),           intent(inout) :: self  !! Walltimer object
+      class(swiftest_parameters), intent(inout) :: param !! Current run configuration parameters
+      ! Internals
+      integer(I8B) :: count_delta
+
+      if (.not.self%lmain_is_started) then
+         write(*,*) "Wall timer error: Cannot start the step time until reset is called at least once!"
+         return
+      end if
+
+      call system_clock(self%count_stop_step)
+
+      count_delta = self%count_stop_step - self%count_start_step
+      self%wall_step = count_delta / (self%count_rate * 1.0_DP)
+
+      return 
+   end subroutine walltime_stop
+
+
    module subroutine walltime_interaction_adapt(self, param, pl, ninteractions)
       !! author: David A. Minton
       !!
@@ -96,7 +121,7 @@ module subroutine walltime_interaction_adapt(self, param, pl, ninteractions)
       logical :: lflatten_final
 
       ! Record the elapsed time 
-      call system_clock(self%count_finish_step)
+      call self%stop(param)
 
       write(schar,'(I1)') self%stage
       write(nstr,*) ninteractions
@@ -108,7 +133,7 @@ module subroutine walltime_interaction_adapt(self, param, pl, ninteractions)
          else
             write(lstyle,*) "TRIANGULAR"
          end if 
-         self%stage1_metric = (self%count_finish_step - self%count_start_step) / real(ninteractions, kind=DP)
+         self%stage1_metric = (self%count_stop_step - self%count_start_step) / real(ninteractions, kind=DP)
          write(mstr,*) self%stage1_metric
       case(2)
          if (.not.self%stage1_is_flattened) then
@@ -117,7 +142,7 @@ module subroutine walltime_interaction_adapt(self, param, pl, ninteractions)
             write(lstyle,*) "TRIANGULAR"
          end if 
 
-         self%stage2_metric = (self%count_finish_step - self%count_start_step) / real(ninteractions, kind=DP)
+         self%stage2_metric = (self%count_stop_step - self%count_start_step) / real(ninteractions, kind=DP)
          self%is_on = .false.
          self%step_counter = 0
          if (self%stage1_metric < self%stage2_metric) then
@@ -129,7 +154,7 @@ module subroutine walltime_interaction_adapt(self, param, pl, ninteractions)
          write(mstr,*) self%stage2_metric
       end select
 
-      write(cstr,*) self%count_finish_step - self%count_start_step
+      write(cstr,*) self%count_stop_step - self%count_start_step
 
       call io_log_one_message(INTERACTION_TIMER_LOG_OUT, adjustl(lstyle) // " " // trim(adjustl(cstr)) // " " // trim(adjustl(nstr)) // " " // trim(adjustl(mstr)))