Repository: giecaruff/stoneforge (language: python)

Issue:
Fix petrophysics range corrector code

Ml scikit



Discussion / hints:

Fix patch:
diff --git a/.gitignore b/.gitignore
index e72a38f..b5a0af9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -120,6 +120,10 @@ venv.bak/
 # mkdocs documentation
 /site
 
+# Local tests
+.ml_project
+.pkl
+
 # mypy
 .mypy_cache/
 .dmypy.json
diff --git a/examples/7-MP-22-BA.las b/examples/7-MP-22-BA.las
new file mode 100644
index 0000000..b480ec3
--- /dev/null
+++ b/examples/7-MP-22-BA.las
@@ -0,0 +1,4052 @@
+~VERSION INFORMATION
+ VERS.                 2.0:   CWLS LOG ASCII STANDARD - VERSION 2.0
+ WRAP.                  NO:   SINGLE LINE PER DEPTH STEP
+ CREA.                 06/02/2020 16:06:00
+#CREATED USING IP VERSION 4.5.2019.2902 BY RMOTA ON 06/02/2020 16:06:00
+~WELL INFORMATION
+#MNEM.UNIT       DATA                          DESCRIPTION MNEMONIC
+#---------      ---------------------------   --------------------------
+ STRT    .M         2400.0250                 : START DEPTH
+ STOP    .M         2799.9250                 : STOP DEPTH
+ STEP    .M         0.1000                    : STEP VALUE
+ NULL    .      -999.0000                     : NULL VALUE
+ DATE    .      06/02/2020                    : LAS file Creation Date
+ WELL   .      7-MP-22-BA       : Well Name
+ COMP   .      PETROBRAS        : Company
+ FLD    .      MASSAPE          : Field
+ STATE  .      BAHIA            : State
+ API    .      20240020649      : API Number
+ UWI    .                       : Unique Well Identifier (UWI)
+ LOC    .      SAD-69, MC=39G   : Location
+ PDAT   .      NM               : Permanent Datum
+ EPDAT  .      0                : Elevation of Permanent Datum
+ LGMEA  .      MR               : Log Measured from
+ DRMEA  .      MR               : Drill Measured From
+ APDAT  .      66.39            : Elevation Above Permanent Datum
+ KB     .      66.69            : KB Elevation
+ DF     .      66.39            : DF Elevation
+ GL     .      56.99            : GL Elevation
+ RWS    .      -999             : Def_Rw
+ WST    .      -999             : Def_Rwt
+ PROV   .                       : Province
+ SRVC   .                       : Contractor
+ GDAT   .      WGS 84           : Geodatum
+ LONG   .      -38.4321144443088: Longitude
+ LATI   .      0                : Latitude
+ COORDIN.                       : Grid System
+ XCOORD .                       : X or East-West Coordinate
+ YCOORD .                       : Y or North-South Coordinate
+~CURVE INFORMATION
+#MNEM              UNIT       API CODE   Curve Type Comments
+#----------  --------------- ----------  ---------- -----------
+ DEPTH      .M                         : Depth       
+ BS         .in                        : BitSize     
+ CALI       .in                        : Caliper     
+ GR         .gAPI                      : GammaRay        
+ DRDN       .                          :             
+ Lith_new   .                          :
+ HDRS       .ôhm.m                     : DeepRes 
+ RHOB       .g/cm3                     : Density     Loaded from DLIS: 7-mp-22-ba_raw-3.dlis
+ NPHI       .m³/m³                     : Neutron     Loaded from DLIS: 7-mp-22-ba_raw-3.dlis
+ DT         .uS/ft                     : Sonic                    
+~A  DEPTH     BS       CALI       GR       HDRS      RHOB      NPHI       DT       DRDN    Lith_new  
+2400.0250    8.5000    9.0217   89.3839    2.8913    2.5691    0.2046   85.5628    3.2013   57.0000 
+2400.1250    8.5000    9.0217   86.8832    2.9390    2.5564    0.2057   85.2066    2.9855   57.0000 
+2400.2250    8.5000    9.0135   86.4069    2.9967    2.5484    0.2043   84.9128    2.7768   57.0000 
+2400.3250    8.5000    9.0217   87.0292    3.0650    2.5463    0.2002   84.5770    2.5992   57.0000 
+2400.4250    8.5000    8.9971   88.9422    3.1357    2.5481    0.1943   84.1087    2.4381   57.0000 
+2400.5250    8.5000    8.9890   90.2790    3.2011    2.5544    0.1906   83.6352    2.4415   57.0000 
+2400.6250    8.5000    9.0053   89.8526    3.2589    2.5610    0.1898   83.1908    2.5444   57.0000 
+2400.7250    8.5000    9.0135   90.4096    3.3092    2.5594    0.1916   82.9740    2.5757   57.0000 
+2400.8250    8.5000    9.0299   90.2828    3.3536    2.5476    0.1948   83.1684    2.4446   57.0000 
+2400.9250    8.5000    9.0053   90.8667    3.3915    2.5350    0.1993   83.7475    2.3430   57.0000 
+2401.0250    8.5000    9.0053   92.6030    3.4183    2.5284    0.2042   84.5214    2.3734   57.0000 
+2401.1250    8.5000    8.9890   92.0076    3.4294    2.5250    0.2092   85.2541    2.4739   57.0000 
+2401.2250    8.5000    9.0135   91.1087    3.4311    2.5252    0.2137   85.6347    2.6259   57.0000 
+2401.3250    8.5000    9.0380   89.5107    3.4482    2.5262    0.2164   85.5515    2.7372   57.0000 
+2401.4250    8.5000    9.0708   87.9857    3.5168    2.5328    0.2170   84.9765    2.8897   57.0000 
+2401.5250    8.5000    9.0380   87.2674    3.6654    2.5346    0.2140   83.8974    2.8266   57.0000 
+2401.6250    8.5000    9.0217   86.1841    3.8990    2.5360    0.2083   82.5765    2.6639   57.0000 
+2401.7250    8.5000    8.9890   84.2865    4.1868    2.5331    0.1995   81.2270    2.3104   57.0000 
+2401.8250    8.5000    8.9726   80.9868    4.4760    2.5310    0.1899   80.0281    1.9507   57.0000 
+2401.9250    8.5000    8.9481   77.6448    4.7155    2.5285    0.1805   79.0857    1.5863   57.0000 
+2402.0250    8.5000    8.9644   73.8112    4.8695    2.5328    0.1725   78.3194    1.4072   57.0000 
+2402.1250    8.5000    9.0135   70.9840    4.9733    2.5453    0.1665   77.6485    1.4572   57.0000 
+2402.2250    8.5000    9.0380   69.6510    5.0337    2.5611    0.1631   77.2995    1.6600   57.0000 
+2402.3250    8.5000    9.1035   69.4590    5.0569    2.5687    0.1636   77.4495    1.8261   57.0000 
+2402.4250    8.5000    9.0953   72.2516    5.0314    2.5639    0.1657   78.3153    1.8021   57.0000 
+2402.5250    8.5000    9.0626   76.0545    4.8586    2.5518    0.1697   79.9959    1.6929   57.0000 
+2402.6250    8.5000    9.0380   81.0214    4.4788    2.5480    0.1759   82.2571    1.8237   57.0000 
+2402.7250    8.5000    9.0135   86.5068    3.9310    2.5541    0.1877   84.9490    2.3379   57.0000 
+2402.8250    8.5000    9.0135   91.3930    3.3592    2.5676    0.2024   87.8367    3.0990   57.0000 
+2402.9250    8.5000    9.0217   97.0128    2.8783    2.5684    0.2176   90.4918    3.6204   57.0000 
+2403.0250    8.5000    9.0135  100.8772    2.5477    2.5600    0.2300   92.6760    3.8670   57.0000 
+2403.1250    8.5000    9.0217  104.8184    2.3560    2.5445    0.2403   93.8046    3.8996   57.0000 
+2403.2250    8.5000    9.0380  107.4305    2.2731    2.5372    0.2464   93.9434    3.9577   57.0000 
+2403.3250    8.5000    9.0544  107.9606    2.2662    2.5374    0.2462   93.3658    3.9558   57.0000 
+2403.4250    8.5000    9.0462  109.1130    2.3027    2.5432    0.2419   92.5403    3.9259   57.0000 
+2403.5250    8.5000    9.0462  108.6060    2.3518    2.5494    0.2357   91.9301    3.8441   57.0000 
+2403.6250    8.5000    9.0053  107.6841    2.3898    2.5517    0.2315   91.4923    3.7508   57.0000 
+2403.7250    8.5000    9.0135  106.9273    2.4075    2.5500    0.2298   91.2709    3.6610   57.0000 
+2403.8250    8.5000    9.0135  105.8056    2.4083    2.5482    0.2314   91.1602    3.6784   57.0000 
+2403.9250    8.5000    9.0217  106.2051    2.4024    2.5493    0.2355   91.0929    3.8338   57.0000 
+2404.0250    8.5000    9.0135  107.0810    2.4005    2.5574    0.2396   91.0230    4.1361   57.0000 
+2404.1250    8.5000    8.9890  108.2487    2.4081    2.5682    0.2417   90.8893    4.4213   57.0000 
+2404.2250    8.5000    8.9890  109.6623    2.4256    2.5761    0.2413   90.7770    4.5640   57.0000 
+2404.3250    8.5000    9.0053  109.5548    2.4484    2.5754    0.2396   90.7413    4.4943   57.0000 
+2404.4250    8.5000    8.9890  110.5996    2.4710    2.5672    0.2377   90.8663    4.2691   57.0000 
+2404.5250    8.5000    8.9890  112.1822    2.4895    2.5594    0.2378   91.0827    4.1163   57.0000 
+2404.6250    8.5000    9.0053  113.4038    2.5056    2.5585    0.2357   91.4112    4.0262   57.0000 
+2404.7250    8.5000    9.0217  113.8071    2.5322    2.5618    0.2326   91.5153    3.9892   57.0000 
+2404.8250    8.5000    9.0544  110.9415    2.5971    2.5673    0.2241   90.9388    3.8161   57.0000 
+2404.9250    8.5000    9.0626  104.5418    2.7487    2.5690    0.2103   89.2077    3.3911   57.0000 
+2405.0250    8.5000    9.0462   94.5429    3.0668    2.5709    0.1880   86.1679    2.6831   57.0000 
+2405.1250    8.5000    9.0380   82.1622    3.6775    2.5692    0.1577   82.3255    1.6423   57.0000 
+2405.2250    8.5000    9.0299   68.8213    4.7859    2.5637    0.1251   78.2031    0.4448   57.0000 
+2405.3250    8.5000    9.0217   57.0207    6.7354    2.5485    0.0964   74.7582   -0.8158   25.0000 
+2405.4250    8.5000    9.0299   48.4930   10.0327    2.5245    0.0799   72.7566   -1.8465   49.0000 
+2405.5250    8.5000    9.0217   44.2790   14.7599    2.4966    0.0778   72.4071   -2.4751   49.0000 
+2405.6250    8.5000    9.0135   44.4480   18.7744    2.4758    0.0869   73.5679   -2.5863   49.0000 
+2405.7250    8.5000    9.0299   46.0691   19.9646    2.4646    0.0991   75.1230   -2.4031   49.0000 
+2405.8250    8.5000    8.9971   47.7708   21.7643    2.4611    0.1071   76.4709   -2.2083   49.0000 
+2405.9250    8.5000    9.0053   48.1357   22.2177    2.4575    0.1084   77.2495   -2.2370   49.0000 
+2406.0250    8.5000    9.0217   45.5505   21.3155    2.4559    0.1054   77.5566   -2.3687   49.0000 
+2406.1250    8.5000    9.0135   42.6157   20.8145    2.4516    0.1026   77.7026   -2.5474   49.0000 
+2406.2250    8.5000    9.0135   40.7412   20.7713    2.4488    0.1039   77.7745   -2.5614   49.0000 
+2406.3250    8.5000    9.0135   40.2572   20.1237    2.4421    0.1105   78.0592   -2.4746   49.0000 
+2406.4250    8.5000    9.0135   43.1151   18.3434    2.4405    0.1214   78.5959   -2.1445   49.0000 
+2406.5250    8.5000    8.9808   48.6005   15.9209    2.4401    0.1325   79.6168   -1.7819   49.0000 
+2406.6250    8.5000    8.9562   55.2230   13.6527    2.4453    0.1402   80.7893   -1.4202   49.0000 
+2406.7250    8.5000    8.9072   60.9927   11.9265    2.4511    0.1430   81.8597   -1.2100   49.0000 
+2406.8250    8.5000    8.8990   64.0196   10.8527    2.4637    0.1433   82.1122   -0.9510   25.0000 
+2406.9250    8.5000    8.8744   62.1412   10.5219    2.4768    0.1435   81.6531   -0.6816   25.0000 
+2407.0250    8.5000    8.8744   56.6404   11.0696    2.4839    0.1405   80.5102   -0.6367   25.0000 
+2407.1250    8.5000    8.8744   51.7005   12.5962    2.4737    0.1320   78.9439   -1.1260   49.0000 
+2407.2250    8.5000    8.8581   48.0282   14.9015    2.4546    0.1188   77.1378   -1.9492   49.0000 
+2407.3250    8.5000    8.8172   47.7746   17.1797    2.4448    0.1070   75.0204   -2.5374   49.0000 
+2407.4250    8.5000    8.7681   49.4341   18.6219    2.4549    0.0987   72.9643   -2.6100   49.0000 
+2407.5250    8.5000    8.7599   50.7709   19.7640    2.4798    0.0928   71.0714   -2.3114   49.0000 
+2407.6250    8.5000    8.7436   52.0155   22.2844    2.5017    0.0875   69.2347   -2.0487   49.0000 
+2407.7250    8.5000    8.7681   52.5955   28.6701    2.5107    0.0851   67.2653   -1.9469   49.0000 
+2407.8250    8.5000    8.7845   52.3766   44.2137    2.4995    0.0871   65.5122   -2.1063   49.0000 
+2407.9250    8.5000    8.8090   50.7171   76.4532    2.4720    0.0964   64.5102   -2.3466   49.0000 
+2408.0250    8.5000    8.8254   48.6082   78.0418    2.4381    0.1113   64.3592   -2.5298   49.0000 
+2408.1250    8.5000    8.8581   45.1549   96.7991    2.4180    0.1282   64.8852   -2.3662   49.0000 
+2408.2250    8.5000    8.8826   42.3853   94.5357    2.4159    0.1388   65.8133   -2.0561   49.0000 
+2408.3250    8.5000    8.8990   41.9397   85.5033    2.4263    0.1410   67.2770   -1.7752   49.0000 
+2408.4250    8.5000    8.8908   42.4237   64.4497    2.4295    0.1386   69.5077   -1.7886   49.0000 
+2408.5250    8.5000    8.8826   45.5044   44.7166    2.4254    0.1382   71.9995   -1.8845   49.0000 
+2408.6250    8.5000    8.8826   49.9949   33.8477    2.4151    0.1433   74.5025   -1.9214   49.0000 
+2408.7250    8.5000    8.8826   55.9912   26.9645    2.4116    0.1525   76.7393   -1.6821   49.0000 
+2408.8250    8.5000    8.8499   64.5613   21.4167    2.4138    0.1666   78.8929   -1.1719   49.0000 
+2408.9250    8.5000    8.8172   73.8458   16.2880    2.4235    0.1822   81.0107   -0.4567   25.0000 
+2409.0250    8.5000    8.8335   82.5233   11.8887    2.4400    0.1980   83.0265    0.4003   57.0000 
+2409.1250    8.5000    8.8008   87.1022    8.7290    2.4651    0.2104   84.5587    1.3148   57.0000 
+2409.2250    8.5000    8.8172   84.7052    6.8313    2.4907    0.2167   85.4128    2.0391   57.0000 
+2409.3250    8.5000    8.8335   77.4297    5.9483    2.4967    0.2165   85.2214    2.1503   57.0000 
+2409.4250    8.5000    8.8172   68.5332    5.8817    2.4765    0.2073   84.2327    1.4398   57.0000 
+2409.5250    8.5000    8.8335   63.6509    6.5496    2.4460    0.1944   83.0403    0.3997   57.0000 
+2409.6250    8.5000    8.8417   67.4154    7.6883    2.4315    0.1845   82.5281   -0.2209   54.0000 
+2409.7250    8.5000    8.8744   77.6026    8.2937    2.4449    0.1915   82.9699    0.2806   54.0000 
+2409.8250    8.5000    8.8581   90.3712    7.5390    2.4730    0.2158   84.2837    1.6546   57.0000 
+2409.9250    8.5000    8.8335  100.1896    6.2614    2.5006    0.2435   85.8418    3.1308   57.0000 
+2410.0250    8.5000    8.8335  102.4637    5.4100    2.5137    0.2528   86.9964    3.7018   57.0000 
+2410.1250    8.5000    8.8499   97.2471    5.2219    2.5114    0.2370   87.6929    3.1297   57.0000 
+2410.2250    8.5000    8.8581   86.2609    5.7839    2.4966    0.2078   88.2423    1.8585   57.0000 
+2410.3250    8.5000    8.8581   71.6946    7.3411    2.4711    0.1790   89.0597    0.3876   57.0000 
+2410.4250    8.5000    8.8417   56.8517   10.4552    2.4392    0.1588   90.1776   -0.9249   25.0000 
+2410.5250    8.5000    8.8335   44.0063   15.8967    2.4012    0.1470   90.5357   -2.0755   49.0000 
+2410.6250    8.5000    8.8663   34.7487   24.5158    2.3686    0.1434   89.1796   -2.8506   49.0000 
+2410.7250    8.5000    8.8744   30.0776   35.6085    2.3459    0.1461   86.1531   -3.2138   49.0000 
+2410.8250    8.5000    8.8990   28.5411   44.9121    2.3340    0.1526   82.9740   -3.2333   49.0000 
+2410.9250    8.5000    8.9072   29.0481   50.6615    2.3242    0.1589   80.6964   -3.2195   49.0000 
+2411.0250    8.5000    8.8990   30.0891   54.5334    2.3124    0.1621   79.9046   -3.3488   49.0000 
+2411.1250    8.5000    8.8744   30.8152   58.5694    2.3001    0.1622   80.3500   -3.5893   49.0000 
+2411.2250    8.5000    8.8744   31.0380   63.6344    2.2940    0.1608   81.3291   -3.7608   49.0000 
+2411.3250    8.5000    8.8499   30.9688   68.3695    2.2927    0.1591   82.3883   -3.8415   49.0000 
+2411.4250    8.5000    8.8499   30.8459   71.5300    2.2940    0.1566   82.6791   -3.9020   49.0000 
+2411.5250    8.5000    8.8254   30.3004   73.3512    2.2944    0.1541   82.3587   -3.9767   49.0000 
+2411.6250    8.5000    8.8744   30.6769   75.7418    2.2939    0.1518   81.6199   -4.0635   49.0000 
+2411.7250    8.5000    8.8663   32.0674   80.0043    2.2971    0.1493   81.1189   -4.0805   49.0000 
+2411.8250    8.5000    8.8417   34.1994   86.4763    2.3051    0.1453   81.0597   -4.0550   49.0000 
+2411.9250    8.5000    8.8744   36.5848   97.8673    2.3210    0.1385   81.1041   -3.9631   49.0000 
+2412.0250    8.5000    8.8744   38.0061  114.2921    2.3386    0.1336   81.2000   -3.7753   49.0000 
+2412.1250    8.5000    8.8826   38.6745  139.0907    2.3510    0.1329   81.3316   -3.5503   49.0000 
+2412.2250    8.5000    8.8908   39.2430  217.1918    2.3562    0.1393   81.7143   -3.2326   49.0000 
+2412.3250    8.5000    8.8663   40.4108  286.7759    2.3580    0.1490   82.4541   -2.8727   49.0000 
+2412.4250    8.5000    8.8663   42.5235  285.6032    2.3647    0.1606   83.6480   -2.3514   49.0000 
+2412.5250    8.5000    8.8908   43.5569  210.6952    2.3666    0.1726   85.0969   -1.9155   49.0000 
+2412.6250    8.5000    8.9072   42.3584  144.9988    2.3588    0.1821   86.6122   -1.7546   49.0000 
+2412.7250    8.5000    8.8908   39.7155  107.2039    2.3421    0.1866   87.6480   -1.9388   49.0000 
+2412.8250    8.5000    8.8499   36.2891   85.1840    2.3329    0.1825   87.9694   -2.2596   49.0000 
+2412.9250    8.5000    8.8172   33.6846   74.8452    2.3344    0.1726   87.4546   -2.5573   49.0000 
+2413.0250    8.5000    8.8417   32.8933   71.4772    2.3377    0.1596   86.4005   -2.9265   49.0000 
+2413.1250    8.5000    8.8744   34.0304   76.3740    2.3404    0.1477   84.9332   -3.2705   49.0000 
+2413.2250    8.5000    8.9153   36.0663   57.2663    2.3491    0.1379   83.6801   -3.4211   49.0000 
+2413.3250    8.5000    8.9153   39.2277   45.7454    2.3716    0.1324   82.6536   -3.1556   49.0000 
+2413.4250    8.5000    8.8908   43.1958   38.9825    2.4008    0.1316   81.4168   -2.5976   49.0000 
+2413.5250    8.5000    8.8744   47.3751   32.6476    2.4243    0.1374   79.6903   -1.9348   49.0000 
+2413.6250    8.5000    8.8335   54.0821   26.4994    2.4390    0.1493   77.2964   -1.2437   49.0000 
+2413.7250    8.5000    8.8417   62.6560   20.7792    2.4469    0.1667   75.6765   -0.5049   25.0000 
+2413.8250    8.5000    8.8254   73.3886   19.5728    2.4534    0.1884   75.7046    0.3474   57.0000 
+2413.9250    8.5000    8.8254   84.6514   14.1091    2.4605    0.2114   77.5352    1.2559   57.0000 
+2414.0250    8.5000    8.8581   92.5876    9.7026    2.4652    0.2335   80.4653    2.0881   57.0000 
+2414.1250    8.5000    8.8581   96.5980    7.5667    2.4700    0.2505   83.7536    2.7492   57.0000 
+2414.2250    8.5000    8.8499   94.6350    6.5772    2.4745    0.2610   86.6893    3.1892   57.0000 
+2414.3250    8.5000    8.8090   89.4454    6.4256    2.4804    0.2617   88.4827    3.3321   57.0000 
+2414.4250    8.5000    8.7845   84.2366    6.9016    2.4813    0.2532   88.4168    3.0639   57.0000 
+2414.5250    8.5000    8.7926   81.2595    8.2384    2.4751    0.2377   86.5122    2.4241   57.0000 
+2414.6250    8.5000    8.8499   84.3249   11.4788    2.4661    0.2228   84.0923    1.7500   57.0000 
+2414.7250    8.5000    8.8826   91.7540   19.3334    2.4647    0.2157   82.4051    1.4837   57.0000 
+2414.8250    8.5000    8.8826  101.1576   28.8904    2.4789    0.2180   81.8577    1.8467   57.0000 
+2414.9250    8.5000    8.8663  109.7161   18.4742    2.5043    0.2293   82.4138    2.7285   57.0000 
+2415.0250    8.5000    8.8335  114.2028    8.6091    2.5320    0.2454   83.6026    3.8182   57.0000 
+2415.1250    8.5000    8.8254  115.5204    4.8496    2.5492    0.2665   85.4745    4.8685   57.0000 
+2415.2250    8.5000    8.7845  114.9442    3.3744    2.5565    0.2827   87.9582    5.5546   57.0000 
+2415.3250    8.5000    8.7845  114.6714    2.7545    2.5553    0.2901   90.6464    5.7771   57.0000 
+2415.4250    8.5000    8.8008  114.3334    2.4949    2.5562    0.2839   93.1270    5.5872   57.0000 
+2415.5250    8.5000    8.8417  114.0875    2.3955    2.5623    0.2757   94.8316    5.4371   57.0000 
+2415.6250    8.5000    8.8663  112.9736    2.3619    2.5736    0.2707   95.7276    5.4956   57.0000 
+2415.7250    8.5000    8.8663  110.1848    2.3440    2.5760    0.2686   95.9143    5.4718   57.0000 
+2415.8250    8.5000    8.8744  109.6162    2.3178    2.5709    0.2679   95.8944    5.3475   57.0000 
+2415.9250    8.5000    8.8663  109.4395    2.2758    2.5590    0.2640   96.1087    4.9796   57.0000 
+2416.0250    8.5000    8.8499  109.7776    2.2219    2.5543    0.2606   96.6974    4.7721   57.0000 
+2416.1250    8.5000    8.8335  110.0388    2.1699    2.5516    0.2506   97.1000    4.3835   57.0000 
+2416.2250    8.5000    8.8172  106.2436    2.1450    2.5546    0.2368   96.8158    3.9844   57.0000 
+2416.3250    8.5000    8.8172   98.4072    2.1771    2.5580    0.2173   95.2388    3.4035   57.0000 
+2416.4250    8.5000    8.8335   89.3302    2.2939    2.5643    0.1968   92.3102    2.8448   57.0000 
+2416.5250    8.5000    8.8254   78.5437    2.5230    2.5647    0.1768   88.4725    2.1882   57.0000 
+2416.6250    8.5000    8.8335   68.9865    2.8953    2.5605    0.1621   84.2592    1.6154   57.0000 
+2416.7250    8.5000    8.8090   64.0158    3.4472    2.5524    0.1539   80.6673    1.1778   57.0000 
+2416.8250    8.5000    8.8008   61.7532    4.1606    2.5481    0.1552   78.2551    1.1350   57.0000 
+2416.9250    8.5000    8.7845   65.0184    4.8220    2.5463    0.1626   77.3663    1.3458   57.0000 
+2417.0250    8.5000    8.7599   71.3873    5.0761    2.5442    0.1738   77.9342    1.6775   57.0000 
+2417.1250    8.5000    8.7517   75.0558    4.8884    2.5402    0.1808   79.4760    1.8288   57.0000 
+2417.2250    8.5000    8.7354   74.5833    4.6266    2.5340    0.1782   81.1648    1.6198   57.0000 
+2417.3250    8.5000    8.7436   68.0069    4.6433    2.5273    0.1636   82.4444    0.9995   57.0000 
+2417.4250    8.5000    8.7272   57.0822    5.1997    2.5201    0.1414   82.7750    0.1160   54.0000 
+2417.5250    8.5000    8.7845   48.0474    6.6454    2.5107    0.1228   81.8469   -0.6928   25.0000 
+2417.6250    8.5000    8.7926   42.8270    9.4251    2.4913    0.1153   79.9133   -1.3301   49.0000 
+2417.7250    8.5000    8.8008   40.9870   14.4678    2.4589    0.1182   77.5408   -1.8830   49.0000 
+2417.8250    8.5000    8.8254   42.2547   21.7899    2.4180    0.1259   76.0561   -2.4431   49.0000 
+2417.9250    8.5000    8.8335   43.6030   31.7584    2.3811    0.1345   75.9541   -2.8956   49.0000 
+2418.0250    8.5000    8.8090   44.4673   40.0934    2.3506    0.1430   77.0204   -3.2212   49.0000 
+2418.1250    8.5000    8.8090   46.3956   44.4547    2.3298    0.1519   78.6071   -3.3390   49.0000 
+2418.2250    8.5000    8.7926   47.1485   41.9807    2.3168    0.1612   80.3827   -3.2907   49.0000 
+2418.3250    8.5000    8.7845   47.8860   37.7924    2.3181    0.1724   82.3725   -2.8931   49.0000 
+2418.4250    8.5000    8.8172   47.7554   34.3060    2.3192    0.1837   84.5306   -2.4918   49.0000 
+2418.5250    8.5000    8.8090   45.6926   32.4854    2.3128    0.1911   86.3673   -2.3729   49.0000 
+2418.6250    8.5000    8.8172   44.9397   32.8799    2.2928    0.1921   87.4439   -2.7423   49.0000 
+2418.7250    8.5000    8.8254   44.1100   35.3850    2.2799    0.1870   87.5265   -3.1702   49.0000 
+2418.8250    8.5000    8.8254   45.0972   38.7261    2.2872    0.1834   86.8102   -3.1427   49.0000 
+2418.9250    8.5000    8.7845   47.0179   40.5945    2.3102    0.1841   85.7571   -2.6573   49.0000 
+2419.0250    8.5000    8.7926   47.4827   38.8364    2.3292    0.1877   84.5612   -2.1590   49.0000 
+2419.1250    8.5000    8.8008   48.2049   34.6587    2.3360    0.1919   83.9122   -1.8833   49.0000 
+2419.2250    8.5000    8.8008   46.3457   29.9359    2.3349    0.1956   83.7980   -1.7805   49.0000 
+2419.3250    8.5000    8.8335   43.4570   26.9148    2.3310    0.2018   84.0745   -1.6528   49.0000 
+2419.4250    8.5000    8.8090   41.2982   26.4857    2.3187    0.2063   84.5286   -1.7486   49.0000 
+2419.5250    8.5000    8.8335   38.5554   29.3944    2.2998    0.2072   84.8153   -2.0966   49.0000 
+2419.6250    8.5000    8.8499   38.2558   35.2532    2.2831    0.2028   84.9541   -2.5786   49.0000 
+2419.7250    8.5000    8.8581   40.7642   41.5423    2.2766    0.1954   84.6388   -2.9562   49.0000 
+2419.8250    8.5000    8.8744   46.0384   44.2666    2.2771    0.1869   83.6510   -3.2282   49.0000 
+2419.9250    8.5000    8.8417   53.6288   42.9598    2.2809    0.1795   82.1225   -3.3996   49.0000 
+2420.0250    8.5000    8.8335   60.9735   38.4918    2.2946    0.1746   80.6122   -3.2858   49.0000 
+2420.1250    8.5000    8.8744   65.2527   33.1444    2.3276    0.1756   79.8010   -2.5953   49.0000 
+2420.2250    8.5000    8.8581   64.0772   26.9087    2.3772    0.1840   79.9745   -1.3233   49.0000 
+2420.3250    8.5000    8.9153   58.5841   21.8555    2.4134    0.1972   80.9694   -0.1597   54.0000 
+2420.4250    8.5000    8.9072   49.8029   18.7932    2.4091    0.2081   82.2602    0.1176   54.0000 
+2420.5250    8.5000    8.9072   41.0485   17.8490    2.3603    0.2088   83.3551   -0.8331   25.0000 
+2420.6250    8.5000    8.8990   34.8101   19.0294    2.2982    0.2030   83.9520   -2.2678   49.0000 
+2420.7250    8.5000    8.9153   30.8613   22.8235    2.2520    0.1957   83.8990   -3.4349   49.0000 
+2420.8250    8.5000    8.8908   29.4476   30.2276    2.2364    0.1919   83.4714   -3.8741   49.0000 
+2420.9250    8.5000    8.8744   29.6013   41.9848    2.2382    0.1905   82.9378   -3.8864   49.0000 
+2421.0250    8.5000    8.8663   30.1237   57.8807    2.2497    0.1901   82.6337   -3.6675   49.0000 
+2421.1250    8.5000    8.8499   30.7691   75.8792    2.2563    0.1909   82.5735   -3.5085   49.0000 
+2421.2250    8.5000    8.8417   31.6603   93.2830    2.2581    0.1916   82.7133   -3.4505   49.0000 
+2421.3250    8.5000    8.8335   32.1980  111.0348    2.2521    0.1909   82.8296   -3.5927   49.0000 
+2421.4250    8.5000    8.8172   33.7000  122.2318    2.2459    0.1891   83.0020   -3.7787   49.0000 
+2421.5250    8.5000    8.8172   35.3595  132.1427    2.2474    0.1863   83.3755   -3.8436   49.0000 
+2421.6250    8.5000    8.7763   36.4658  133.5091    2.2562    0.1841   83.8173   -3.7388   49.0000 
+2421.7250    8.5000    8.7517   36.5580  125.2786    2.2656    0.1825   84.3224   -3.6047   49.0000 
+2421.8250    8.5000    8.7926   35.0445  111.7664    2.2689    0.1817   84.5765   -3.5643   49.0000 
+2421.9250    8.5000    8.8254   32.9701  100.5336    2.2671    0.1812   84.5673   -3.6175   49.0000 
+2422.0250    8.5000    8.8581   31.9099   95.9071    2.2634    0.1785   84.3571   -3.7834   49.0000 
+2422.1250    8.5000    8.8663   32.8319   99.2309    2.2576    0.1756   84.0969   -3.9953   49.0000 
+2422.2250    8.5000    8.8417   34.6565  107.9531    2.2537    0.1726   83.8163   -4.1736   49.0000 
+2422.3250    8.5000    8.8417   36.9767  118.6181    2.2556    0.1736   83.7245   -4.1010   49.0000 
+2422.4250    8.5000    8.8254   38.1752  124.4517    2.2643    0.1761   83.7704   -3.8445   49.0000 
+2422.5250    8.5000    8.8254   38.3903  124.8630    2.2698    0.1801   83.8725   -3.6009   49.0000 
+2422.6250    8.5000    8.8172   38.3826  124.8767    2.2677    0.1804   83.7959   -3.6317   49.0000 
+2422.7250    8.5000    8.8335   38.8512  124.8456    2.2594    0.1773   83.4949   -3.9016   49.0000 
+2422.8250    8.5000    8.8417   40.4146  117.4706    2.2565    0.1705   83.0459   -4.1856   49.0000 
+2422.9250    8.5000    8.8172   42.1356   98.8093    2.2636    0.1666   82.8929   -4.1739   49.0000 
+2423.0250    8.5000    8.8254   43.3955   81.3173    2.2784    0.1655   83.0765   -3.9163   49.0000 
+2423.1250    8.5000    8.8335   43.7220   70.8177    2.2920    0.1699   83.2143   -3.4967   49.0000 
+2423.2250    8.5000    8.8172   43.2380   66.5123    2.2926    0.1748   83.1020   -3.3194   49.0000 
+2423.3250    8.5000    8.8090   43.0383   65.5155    2.2834    0.1799   82.3163   -3.3353   49.0000 
+2423.4250    8.5000    8.8090   43.3033   64.2878    2.2670    0.1826   81.2806   -3.5713   49.0000 
+2423.5250    8.5000    8.7681   43.7336   59.4506    2.2637    0.1837   80.3520   -3.6028   49.0000 
+2423.6250    8.5000    8.7763   43.1458   54.1089    2.2706    0.1856   79.8520   -3.4007   49.0000 
+2423.7250    8.5000    8.7845   41.4249   50.2311    2.2907    0.1869   79.8316   -2.9542   49.0000 
+2423.8250    8.5000    8.7436   39.6387   48.1260    2.3033    0.1893   80.0255   -2.6249   49.0000 
+2423.9250    8.5000    8.7517   37.8448   47.5788    2.3022    0.1896   80.2153   -2.6358   49.0000 
+2424.0250    8.5000    8.7108   37.4146   47.8418    2.2846    0.1882   80.2061   -3.0333   49.0000 
+2424.1250    8.5000    8.7436   37.5452   48.2348    2.2651    0.1858   80.1571   -3.5053   49.0000 
+2424.2250    8.5000    8.7763   37.0035   48.6223    2.2558    0.1845   80.1388   -3.7343   49.0000 
+2424.3250    8.5000    8.8335   35.6821   49.2514    2.2524    0.1864   80.4755   -3.7382   49.0000 
+2424.4250    8.5000    8.8581   33.3620   50.0952    2.2485    0.1892   81.1980   -3.7236   49.0000 
+2424.5250    8.5000    8.8335   30.8766   51.1030    2.2373    0.1918   82.2571   -3.8617   49.0000 
+2424.6250    8.5000    8.8417   29.4361   52.1004    2.2244    0.1940   83.4500   -4.0452   49.0000 
+2424.7250    8.5000    8.8335   29.9432   53.0819    2.2124    0.1950   84.3061   -4.2517   49.0000 
+2424.8250    8.5000    8.8417   31.8485   54.3002    2.2029    0.1938   84.6582   -4.4828   49.0000 
+2424.9250    8.5000    8.8335   33.7384   55.6886    2.1989    0.1893   84.3929   -4.7113   49.0000 
+2425.0250    8.5000    8.8172   35.2596   57.2283    2.2023    0.1830   83.6939   -4.8539   49.0000 
+2425.1250    8.5000    8.8254   35.5515   58.3709    2.2157    0.1759   82.7041   -4.8232   49.0000 
+2425.2250    8.5000    8.8417   35.4286   58.7318    2.2341    0.1673   81.5357   -4.7424   49.0000 
+2425.3250    8.5000    8.8417   36.2468   58.3996    2.2518    0.1590   80.3571   -4.6652   49.0000 
+2425.4250    8.5000    8.8663   36.7692   57.6700    2.2618    0.1520   79.1225   -4.6986   49.0000 
+2425.5250    8.5000    8.8826   37.4299   56.5641    2.2614    0.1473   77.9184   -4.8599   49.0000 
+2425.6250    8.5000    8.8744   38.1982   53.6668    2.2602    0.1452   76.7857   -4.9560   49.0000 
+2425.7250    8.5000    8.8417   38.1982   49.5806    2.2707    0.1438   76.0510   -4.7925   49.0000 
+2425.8250    8.5000    8.8008   38.7590   44.8506    2.2998    0.1425   75.8051   -4.2526   49.0000 
+2425.9250    8.5000    8.7926   39.7885   39.0652    2.3323    0.1380   76.1633   -3.7524   49.0000 
+2426.0250    8.5000    8.8254   40.6413   33.2143    2.3587    0.1307   76.5459   -3.4698   49.0000 
+2426.1250    8.5000    8.8581   42.4967   28.1813    2.3758    0.1206   76.6684   -3.4637   49.0000 
+2426.2250    8.5000    8.8826   45.2163   24.3932    2.3958    0.1090   76.1939   -3.4527   49.0000 
+2426.3250    8.5000    8.8908   48.9693   21.7911    2.4158    0.0973   75.0903   -3.4415   49.0000 
+2426.4250    8.5000    8.8908   54.4854   19.9498    2.4410    0.0893   73.7827   -3.2043   49.0000 
+2426.5250    8.5000    8.8581   61.0695   18.3838    2.4670    0.0897   72.2796   -2.6708   49.0000 
+2426.6250    8.5000    8.8254   68.5562   16.3835    2.4993    0.1004   71.0031   -1.6682   49.0000 
+2426.7250    8.5000    8.8090   76.3964   14.0449    2.5303    0.1208   70.2571   -0.3664   25.0000 
+2426.8250    8.5000    8.7926   84.6745   11.3863    2.5584    0.1478   70.2536    1.0956   57.0000 
+2426.9250    8.5000    8.7845   92.9449    8.9973    2.5762    0.1760   71.2872    2.3906   57.0000 
+2427.0250    8.5000    8.8172  100.1589    6.9477    2.5804    0.1989   73.2857    3.2371   57.0000 
+2427.1250    8.5000    8.8008  105.4714    5.3736    2.5712    0.2116   76.0423    3.4783   57.0000 
+2427.2250    8.5000    8.7763  107.5842    4.3069    2.5652    0.2152   78.9469    3.4768   57.0000 
+2427.3250    8.5000    8.8008  106.7391    3.6880    2.5639    0.2133   81.3939    3.3880   57.0000 
+2427.4250    8.5000    8.7681  104.3690    3.4058    2.5701    0.2104   82.8485    3.4176   57.0000 
+2427.5250    8.5000    8.7926  102.3984    3.3429    2.5663    0.2113   83.4638    3.3678   57.0000 
+2427.6250    8.5000    8.8008  100.4777    3.3968    2.5647    0.2139   83.4934    3.4216   57.0000 
+2427.7250    8.5000    8.7845   98.6723    3.4774    2.5621    0.2178   83.3985    3.5026   57.0000 
+2427.8250    8.5000    8.8090   96.8553    3.5163    2.5655    0.2169   83.3490    3.5398   57.0000 
+2427.9250    8.5000    8.8335   94.6274    3.4932    2.5655    0.2140   83.4204    3.4438   57.0000 
+2428.0250    8.5000    8.8090   93.3251    3.4383    2.5645    0.2105   83.7429    3.3060   57.0000 
+2428.1250    8.5000    8.8008   92.9871    3.3948    2.5662    0.2093   84.2872    3.3024   57.0000 
+2428.2250    8.5000    8.7681   93.3021    3.3801    2.5696    0.2106   85.1515    3.4121   57.0000 
+2428.3250    8.5000    8.7763   93.3789    3.3743    2.5770    0.2113   86.0260    3.5848   57.0000 
+2428.4250    8.5000    8.8090   92.9449    3.3406    2.5820    0.2109   86.8281    3.6699   57.0000 
+2428.5250    8.5000    8.8090   92.0844    3.2607    2.5831    0.2063   87.3883    3.5370   57.0000 
+2428.6250    8.5000    8.8499   91.0972    3.1627    2.5814    0.2005   87.7071    3.3103   57.0000 
+2428.7250    8.5000    8.8417   91.2969    3.1030    2.5790    0.1969   87.5827    3.1425   57.0000 
+2428.8250    8.5000    8.8090   92.8911    3.1258    2.5827    0.1989   86.9408    3.2855   57.0000 
+2428.9250    8.5000    8.8417   95.6568    3.2317    2.5854    0.2068   85.9704    3.5991   57.0000 
+2429.0250    8.5000    8.8008   98.7568    3.3662    2.5849    0.2149   85.2495    3.8623   57.0000 
+2429.1250    8.5000    8.8172  101.1845    3.4370    2.5776    0.2219   85.2128    3.9486   57.0000 
+2429.2250    8.5000    8.8008  102.8978    3.3762    2.5683    0.2267   86.0275    3.9214   57.0000 
+2429.3250    8.5000    8.8335  103.6122    3.2016    2.5626    0.2326   87.4929    4.0038   57.0000 
+2429.4250    8.5000    8.8663  103.0668    2.9937    2.5626    0.2394   89.2862    4.2321   57.0000 
+2429.5250    8.5000    8.8663  101.9144    2.8216    2.5640    0.2461   91.0357    4.4842   57.0000 
+2429.6250    8.5000    8.8990   99.8170    2.7118    2.5666    0.2495   92.3679    4.6502   57.0000 
+2429.7250    8.5000    8.8826   98.2805    2.6617    2.5674    0.2467   93.0781    4.5722   57.0000 
+2429.8250    8.5000    8.8663   98.5148    2.6586    2.5718    0.2406   93.1699    4.4557   57.0000 
+2429.9250    8.5000    8.8663   99.3753    2.6849    2.5763    0.2352   92.7949    4.3650   57.0000 
+2430.0250    8.5000    8.8744  101.0117    2.7203    2.5828    0.2341   92.1041    4.4589   57.0000 
+2430.1250    8.5000    8.8581  102.2985    2.7481    2.5888    0.2334   91.4444    4.5566   57.0000 
+2430.2250    8.5000    8.8663  103.3088    2.7622    2.5925    0.2307   90.8827    4.5397   57.0000 
+2430.3250    8.5000    8.8908  103.8043    2.7645    2.5925    0.2262   90.5566    4.3879   57.0000 
+2430.4250    8.5000    8.8663  104.0271    2.7583    2.5827    0.2237   90.3281    4.1099   57.0000 
+2430.5250    8.5000    8.8663  103.1052    2.7432    2.5711    0.2233   90.1087    3.8656   57.0000 
+2430.6250    8.5000    8.8908  100.2626    2.7185    2.5630    0.2233   89.9041    3.7032   57.0000 
+2430.7250    8.5000    8.9072   97.6735    2.6912    2.5668    0.2208   89.7531    3.6976   57.0000 
+2430.8250    8.5000    8.9072   94.9846    2.6759    2.5753    0.2188   89.6837    3.7982   57.0000 
+2430.9250    8.5000    8.9072   93.9667    2.6845    2.5818    0.2194   89.8122    3.9473   57.0000 
+2431.0250    8.5000    8.9317   94.7003    2.7187    2.5813    0.2234   90.0638    4.0731   57.0000 
+2431.1250    8.5000    8.8990   95.6876    2.7633    2.5757    0.2277   90.4362    4.1056   57.0000 
+2431.2250    8.5000    8.9153   97.6082    2.7903    2.5707    0.2317   90.8475    4.1361   57.0000 
+2431.3250    8.5000    8.9235   98.4149    2.7858    2.5673    0.2326   91.1403    4.0991   57.0000 
+2431.4250    8.5000    8.9153   99.2600    2.7664    2.5677    0.2321   91.2934    4.0916   57.0000 
+2431.5250    8.5000    8.8990   99.5059    2.7592    2.5627    0.2283   91.2923    3.8629   57.0000 
+2431.6250    8.5000    8.8826   97.4930    2.7721    2.5592    0.2273   91.2189    3.7619   57.0000 
+2431.7250    8.5000    8.8417   94.6427    2.7917    2.5577    0.2253   91.1867    3.6641   57.0000 
+2431.8250    8.5000    8.8499   90.6477    2.7989    2.5669    0.2235   91.1403    3.7890   57.0000 
+2431.9250    8.5000    8.8663   87.4210    2.7863    2.5760    0.2180   90.9362    3.7852   57.0000 
+2432.0250    8.5000    8.8908   87.1444    2.7675    2.5803    0.2141   90.5847    3.7430   57.0000 
+2432.1250    8.5000    8.8663   90.0408    2.7669    2.5803    0.2144   90.0469    3.7522   57.0000 
+2432.2250    8.5000    8.8581   93.4865    2.7977    2.5823    0.2169   89.4597    3.8770   57.0000 
+2432.3250    8.5000    8.8663   95.9603    2.8496    2.5898    0.2196   88.8347    4.1151   57.0000 
+2432.4250    8.5000    8.8499   97.0743    2.8922    2.5952    0.2188   88.3296    4.1981   57.0000 
+2432.5250    8.5000    8.9072   96.1908    2.8956    2.5963    0.2188   88.0480    4.2205   57.0000 
+2432.6250    8.5000    8.8990   96.9744    2.8563    2.5973    0.2218   88.0837    4.3378   57.0000 
+2432.7250    8.5000    8.8990   99.9092    2.7980    2.5984    0.2260   88.3801    4.4998   57.0000 
+2432.8250    8.5000    8.8826  103.3702    2.7461    2.6012    0.2292   88.8332    4.6642   57.0000 
+2432.9250    8.5000    8.8663  107.5112    2.7061    2.5954    0.2296   89.5510    4.5628   57.0000 
+2433.0250    8.5000    8.8417  109.1822    2.6639    2.5908    0.2328   90.5255    4.5769   57.0000 
+2433.1250    8.5000    8.8663  108.5829    2.5975    2.5832    0.2370   91.6454    4.5629   57.0000 
+2433.2250    8.5000    8.8826  106.3857    2.4928    2.5828    0.2412   92.6786    4.6962   57.0000 
+2433.3250    8.5000    8.8990  103.6314    2.3576    2.5839    0.2424   93.4714    4.7568   57.0000 
+2433.4250    8.5000    8.9072  102.2793    2.2189    2.5866    0.2441   94.0592    4.8702   57.0000 
+2433.5250    8.5000    8.8744  101.9144    2.1105    2.5828    0.2474   94.6622    4.9044   57.0000 
+2433.6250    8.5000    8.8417  103.4855    2.0457    2.5710    0.2501   95.2837    4.7567   57.0000 
+2433.7250    8.5000    8.8335  104.1692    2.0176    2.5606    0.2522   95.7974    4.6180   57.0000 
+2433.8250    8.5000    8.8335  103.5008    2.0084    2.5560    0.2511   96.1704    4.4904   57.0000 
+2433.9250    8.5000    8.8335  101.2037    2.0074    2.5609    0.2494   96.1648    4.5309   57.0000 
+2434.0250    8.5000    8.8499   96.3790    2.0251    2.5662    0.2437   95.7015    4.4467   57.0000 
+2434.1250    8.5000    8.8254   92.8143    2.0819    2.5725    0.2366   94.7117    4.3374   57.0000 
+2434.2250    8.5000    8.8335   90.1714    2.1856    2.5770    0.2292   93.2087    4.1813   57.0000 
+2434.3250    8.5000    8.8581   89.7604    2.3229    2.5817    0.2241   91.5939    4.1038   57.0000 
+2434.4250    8.5000    8.8663   91.3584    2.4640    2.5797    0.2210   90.0867    3.9586   57.0000 
+2434.5250    8.5000    8.8663   92.4071    2.5862    2.5740    0.2188   88.9750    3.7718   57.0000 
+2434.6250    8.5000    8.8581   93.6363    2.6817    2.5669    0.2180   88.2184    3.6031   57.0000 
+2434.7250    8.5000    8.8417   94.8732    2.7601    2.5673    0.2191   87.7969    3.6498   57.0000 
+2434.8250    8.5000    8.8581   95.3956    2.8372    2.5687    0.2215   87.6765    3.7591   57.0000 
+2434.9250    8.5000    8.8744   95.9949    2.9189    2.5676    0.2220   87.7286    3.7539   57.0000 
+2435.0250    8.5000    8.8417   96.5557    2.9978    2.5623    0.2205   87.9230    3.5955   57.0000 
+2435.1250    8.5000    8.8663   95.8527    3.0603    2.5619    0.2174   88.2184    3.4848   57.0000 
+2435.2250    8.5000    8.8499   96.4059    3.0998    2.5698    0.2150   88.6566    3.5630   57.0000 
+2435.3250    8.5000    8.8581   97.4738    3.1274    2.5777    0.2141   89.1908    3.6903   57.0000 
+2435.4250    8.5000    8.8826   98.3381    3.1609    2.5826    0.2136   89.5510    3.7701   57.0000 
+2435.5250    8.5000    8.8826  100.0744    3.2017    2.5808    0.2144   89.5995    3.7638   57.0000 
+2435.6250    8.5000    8.8908  100.2511    3.2315    2.5800    0.2137   89.5046    3.7222   57.0000 
+2435.7250    8.5000    8.9072   99.1793    3.2251    2.5782    0.2156   89.4918    3.7486   57.0000 
+2435.8250    8.5000    8.8826   96.7478    3.1706    2.5770    0.2174   89.8342    3.7880   57.0000 
+2435.9250    8.5000    8.8663   93.7016    3.0835    2.5773    0.2224   90.4464    3.9586   57.0000 
+2436.0250    8.5000    8.8335   91.6849    2.9978    2.5791    0.2253   91.0954    4.0927   57.0000 
+2436.1250    8.5000    8.8254   90.6900    2.9407    2.5819    0.2283   91.4923    4.2484   57.0000 
+2436.2250    8.5000    8.8499   92.7105    2.9213    2.5831    0.2296   91.4949    4.3155   57.0000 
+2436.3250    8.5000    8.8826   94.1702    2.9373    2.5824    0.2284   91.1383    4.2597   57.0000 
+2436.4250    8.5000    8.8908   94.5160    2.9822    2.5820    0.2244   90.4903    4.1196   57.0000 
+2436.5250    8.5000    8.9235   94.4238    3.0479    2.5805    0.2183   89.7852    3.8851   57.0000 
+2436.6250    8.5000    8.8990   92.8911    3.1256    2.5779    0.2131   89.0184    3.6590   57.0000 
+2436.7250    8.5000    8.8990   92.0383    3.2078    2.5723    0.2085   88.3230    3.3970   57.0000 
+2436.8250    8.5000    8.8744   91.2355    3.2896    2.5691    0.2037   87.6204    3.1714   57.0000 
+2436.9250    8.5000    8.8826   90.8513    3.3698    2.5689    0.1977   86.9704    2.9688   57.0000 
+2437.0250    8.5000    8.8826   89.3033    3.4537    2.5728    0.1914   86.2760    2.8363   57.0000 
+2437.1250    8.5000    8.8744   87.6285    3.5548    2.5788    0.1857   85.4276    2.7652   57.0000 
+2437.2250    8.5000    8.8990   88.5504    3.6886    2.5851    0.1838   84.4148    2.8303   57.0000 
+2437.3250    8.5000    8.8908   90.9128    3.8591    2.5886    0.1860   83.3066    2.9731   57.0000 
+2437.4250    8.5000    8.8990   93.6978    4.0521    2.5849    0.1926   82.4515    3.1185   57.0000 
+2437.5250    8.5000    8.9235   95.6760    4.2383    2.5799    0.1999   81.9490    3.2622   57.0000 
+2437.6250    8.5000    8.9072   94.4622    4.3771    2.5776    0.2074   81.9321    3.4628   57.0000 
+2437.7250    8.5000    8.9072   91.2892    4.4213    2.5801    0.2129   82.3423    3.6983   57.0000 
+2437.8250    8.5000    8.9235   88.7232    4.3401    2.5810    0.2152   83.1495    3.7940   57.0000 
+2437.9250    8.5000    8.8499   88.1086    4.1523    2.5819    0.2146   83.9408    3.7925   57.0000 
+2438.0250    8.5000    8.8744   89.2303    3.9300    2.5847    0.2152   84.4133    3.8681   57.0000 
+2438.1250    8.5000    8.8335   91.1471    3.7488    2.5892    0.2192   84.4878    4.0907   57.0000 
+2438.2250    8.5000    8.7926   93.8168    3.6453    2.5888    0.2240   84.4327    4.2424   57.0000 
+2438.3250    8.5000    8.8172   96.1063    3.6130    2.5832    0.2255   84.7291    4.1797   57.0000 
+2438.4250    8.5000    8.8254   97.8426    3.6183    2.5788    0.2245   85.3908    4.0594   57.0000 
+2438.5250    8.5000    8.8335   98.6838    3.6203    2.5782    0.2242   86.3179    4.0362   57.0000 
+2438.6250    8.5000    8.8499   98.6915    3.5893    2.5806    0.2277   87.3770    4.2024   57.0000 
+2438.7250    8.5000    8.8581   98.2267    3.5221    2.5783    0.2317   88.3893    4.2875   57.0000 
+2438.8250    8.5000    8.8254   98.0884    3.4398    2.5739    0.2332   89.1959    4.2518   57.0000 
+2438.9250    8.5000    8.8417   99.2677    3.3681    2.5692    0.2296   89.5469    4.0375   57.0000 
+2439.0250    8.5000    8.8581   99.9092    3.3219    2.5706    0.2244   89.2551    3.8941   57.0000 
+2439.1250    8.5000    8.8417   99.2754    3.3033    2.5764    0.2208   88.4179    3.8875   57.0000 
+2439.2250    8.5000    8.8990   96.8937    3.3080    2.5809    0.2182   87.4725    3.8903   57.0000 
+2439.3250    8.5000    8.8908   92.2265    3.3344    2.5803    0.2166   86.5270    3.8242   57.0000 
+2439.4250    8.5000    8.8826   89.3993    3.3879    2.5757    0.2129   85.8378    3.6112   57.0000 
+2439.5250    8.5000    8.8826   89.2572    3.4671    2.5737    0.2120   85.4051    3.5414   57.0000 
+2439.6250    8.5000    8.8581   93.1408    3.5445    2.5745    0.2138   85.3786    3.6171   57.0000 
+2439.7250    8.5000    8.8417   99.2446    3.5624    2.5742    0.2205   85.7980    3.8342   57.0000 
+2439.8250    8.5000    8.8744  103.4663    3.4822    2.5679    0.2272   86.5245    3.9312   57.0000 
+2439.9250    8.5000    8.8744  105.8901    3.3388    2.5629    0.2276   87.2398    3.8425   57.0000 
+2440.0250    8.5000    8.8826  103.9003    3.2096    2.5631    0.2223   87.5862    3.6729   57.0000 
+2440.1250    8.5000    8.8581  100.2895    3.1519    2.5740    0.2142   87.4286    3.6194   57.0000 
+2440.2250    8.5000    8.8499   96.9398    3.1869    2.5831    0.2097   86.7031    3.6533   57.0000 
+2440.3250    8.5000    8.8254   93.5364    3.3006    2.5863    0.2089   85.6929    3.6898   57.0000 
+2440.4250    8.5000    8.8826   92.8027    3.4480    2.5790    0.2110   84.6791    3.6133   57.0000 
+2440.5250    8.5000    8.8581   93.7823    3.5687    2.5721    0.2146   84.0617    3.5966   57.0000 
+2440.6250    8.5000    8.8254   95.9526    3.6175    2.5691    0.2173   83.9122    3.6258   57.0000 
+2440.7250    8.5000    8.8417   98.1614    3.5915    2.5733    0.2185   84.1709    3.7484   57.0000 
+2440.8250    8.5000    8.7845   99.1985    3.5274    2.5791    0.2192   84.6077    3.8886   57.0000 
+2440.9250    8.5000    8.8090   99.4367    3.4737    2.5867    0.2216   85.1148    4.1217   57.0000 
+2441.0250    8.5000    8.8663   98.5378    3.4590    2.5929    0.2259   85.6061    4.3876   57.0000 
+2441.1250    8.5000    8.8417   98.5878    3.4763    2.5953    0.2286   85.9643    4.5260   57.0000 
+2441.2250    8.5000    8.8990  100.5315    3.4882    2.5912    0.2280   86.1929    4.4232   57.0000 
+2441.3250    8.5000    8.8417  102.5098    3.4578    2.5806    0.2245   86.4740    4.0965   57.0000 
+2441.4250    8.5000    8.8417  104.2576    3.3807    2.5699    0.2226   87.0153    3.8183   57.0000 
+2441.5250    8.5000    8.8663  104.6033    3.2767    2.5641    0.2242   87.7740    3.7561   57.0000 
+2441.6250    8.5000    8.8744  102.3561    3.1580    2.5670    0.2269   88.6878    3.9029   57.0000 
+2441.7250    8.5000    8.8744   99.2062    3.0278    2.5709    0.2287   89.5286    4.0398   57.0000 
+2441.8250    8.5000    8.8744   96.4405    2.8970    2.5758    0.2280   90.2755    4.1161   57.0000 
+2441.9250    8.5000    8.8499   94.2125    2.7893    2.5768    0.2283   90.7449    4.1476   57.0000 
+2442.0250    8.5000    8.8581   93.8284    2.7273    2.5837    0.2308   90.8179    4.3667   57.0000 
+2442.1250    8.5000    8.8744   94.8578    2.7167    2.5877    0.2336   90.4709    4.5406   57.0000 
+2442.2250    8.5000    8.8908   95.6722    2.7458    2.5900    0.2346   89.8959    4.6213   57.0000 
+2442.3250    8.5000    8.8744   96.5519    2.7979    2.5868    0.2309   89.3036    4.4326   57.0000 
+2442.4250    8.5000    8.8826   95.5224    2.8598    2.5862    0.2277   88.8301    4.3123   57.0000 
+2442.5250    8.5000    8.8826   92.7835    2.9220    2.5883    0.2238   88.6061    4.2255   57.0000 
+2442.6250    8.5000    8.8744   91.1241    2.9744    2.5905    0.2222   88.4985    4.2172   57.0000 
+2442.7250    8.5000    8.8826   90.8744    3.0068    2.5860    0.2192   88.6225    4.0260   57.0000 
+2442.8250    8.5000    8.8417   91.2124    3.0174    2.5765    0.2193   88.7031    3.8386   57.0000 
+2442.9250    8.5000    8.8417   93.3059    3.0169    2.5675    0.2197   88.8138    3.6728   57.0000 
+2443.0250    8.5000    8.8335   94.2701    3.0201    2.5657    0.2212   88.8173    3.6859   57.0000 
+2443.1250    8.5000    8.8254   93.5479    3.0363    2.5734    0.2204   88.8929    3.8164   57.0000 
+2443.2250    8.5000    8.8417   94.0857    3.0682    2.5817    0.2192   89.1954    3.9404   57.0000 
+2443.3250    8.5000    8.8090   93.8706    3.1133    2.5826    0.2179   89.6214    3.9169   57.0000 
+2443.4250    8.5000    8.8335   93.1408    3.1620    2.5754    0.2185   90.0158    3.7915   57.0000 
+2443.5250    8.5000    8.8581   90.9743    3.1950    2.5671    0.2184   90.1133    3.6199   57.0000 
+2443.6250    8.5000    8.9153   87.5055    3.1903    2.5698    0.2150   89.7704    3.5649   57.0000 
+2443.7250    8.5000    8.8908   83.2839    3.1496    2.5800    0.2046   88.9102    3.4221   57.0000 
+2443.8250    8.5000    8.8663   80.2108    3.1151    2.5924    0.1920   87.3908    3.2475   57.0000 
+2443.9250    8.5000    8.8499   80.8216    3.1525    2.5976    0.1792   85.3179    2.9233   57.0000 
+2444.0250    8.5000    8.8663   82.3389    3.3178    2.5972    0.1712   83.1342    2.6511   57.0000 
+2444.1250    8.5000    8.9072   85.4696    3.6296    2.5960    0.1696   81.5306    2.5735   57.0000 
+2444.2250    8.5000    8.9317   89.3263    4.0289    2.5949    0.1757   80.9714    2.7546   57.0000 
+2444.3250    8.5000    8.9072   91.4467    4.3518    2.5954    0.1871   81.4179    3.1446   57.0000 
+2444.4250    8.5000    8.8990   94.2279    4.4272    2.5942    0.1985   82.4730    3.5029   57.0000 
+2444.5250    8.5000    8.8826   96.4597    4.2452    2.5944    0.2091   83.8367    3.8579   57.0000 
+2444.6250    8.5000    8.8663   97.3194    3.9424    2.5915    0.2160   85.2597    4.0318   57.0000 
+2444.7250    8.5000    8.8417   97.2587    3.6400    2.5881    0.2220   86.7949    4.1627   57.0000 
+2444.8250    8.5000    8.8254   95.2082    3.3710    2.5794    0.2246   88.1240    4.0749   57.0000 
+2444.9250    8.5000    8.8663   92.5507    3.1172    2.5730    0.2271   89.0878    4.0294   57.0000 
+2445.0250    8.5000    8.8908   90.4979    2.8767    2.5666    0.2257   89.4867    3.8565   57.0000 
+2445.1250    8.5000    8.9235   88.8953    2.6891    2.5683    0.2224   89.4811    3.7799   57.0000 
+2445.2250    8.5000    8.9562   88.0418    2.5958    2.5739    0.2157   89.2862    3.6685   57.0000 
+2445.3250    8.5000    8.9153   88.4328    2.6089    2.5776    0.2089   88.9117    3.5166   57.0000 
+2445.4250    8.5000    8.9235   87.8628    2.7181    2.5777    0.2025   88.4097    3.3050   57.0000 
+2445.5250    8.5000    8.8826   87.6707    2.8936    2.5697    0.1988   87.6117    3.0211   57.0000 
+2445.6250    8.5000    8.8663   88.6387    3.0819    2.5693    0.1969   86.7505    2.9497   57.0000 
+2445.7250    8.5000    8.8908   88.0472    3.2276    2.5740    0.1947   86.1168    2.9698   57.0000 
+2445.8250    8.5000    8.8663   88.5081    3.3071    2.5862    0.1906   85.7862    3.0765   57.0000 
+2445.9250    8.5000    8.8417   89.1919    3.3403    2.5911    0.1866   85.7337    3.0433   57.0000 
+2446.0250    8.5000    8.8826   88.1086    3.3692    2.5879    0.1850   85.7138    2.9246   57.0000 
+2446.1250    8.5000    8.8417   88.3545    3.4215    2.5829    0.1874   85.5745    2.9052   57.0000 
+2446.2250    8.5000    8.8663   89.6605    3.4952    2.5829    0.1952   85.5903    3.1639   57.0000 
+2446.3250    8.5000    8.8990   91.8078    3.5602    2.5900    0.2069   85.9495    3.6955   57.0000 
+2446.4250    8.5000    8.8581   95.7874    3.5699    2.5958    0.2197   86.6372    4.2384   57.0000 
+2446.5250    8.5000    8.8908   99.3253    3.4794    2.6010    0.2266   87.7005    4.5720   57.0000 
+2446.6250    8.5000    8.8254  101.0770    3.2825    2.6005    0.2317   88.7602    4.7321   57.0000 
+2446.7250    8.5000    8.8008  101.5840    3.0271    2.5993    0.2359   89.8760    4.8486   57.0000 
+2446.8250    8.5000    8.8008  101.5072    2.7795    2.5934    0.2434   90.9602    4.9811   57.0000 
+2446.9250    8.5000    8.8090  101.5033    2.5862    2.5857    0.2459   91.7122    4.9123   57.0000 
+2447.0250    8.5000    8.8335  102.2486    2.4658    2.5741    0.2454   92.0337    4.6610   57.0000 
+2447.1250    8.5000    8.8744  102.7326    2.4143    2.5635    0.2408   91.7071    4.2974   57.0000 
+2447.2250    8.5000    8.8172  103.1436    2.4136    2.5580    0.2385   91.0975    4.1098   57.0000 
+2447.3250    8.5000    8.8254  104.2960    2.4405    2.5606    0.2358   90.6367    4.0710   57.0000 
+2447.4250    8.5000    8.8581  105.3908    2.4761    2.5659    0.2353   90.6087    4.1598   57.0000 
+2447.5250    8.5000    8.8908  106.8697    2.5130    2.5712    0.2356   90.9888    4.2764   57.0000 
+2447.6250    8.5000    8.8908  106.9158    2.5526    2.5732    0.2374   91.2602    4.3786   57.0000 
+2447.7250    8.5000    8.8908  103.6852    2.5974    2.5729    0.2388   90.9842    4.4174   57.0000 
+2447.8250    8.5000    8.8335   98.7491    2.6479    2.5723    0.2390   90.3372    4.4112   57.0000 
+2447.9250    8.5000    8.8254   93.0563    2.7041    2.5716    0.2373   89.4725    4.3400   57.0000 
+2448.0250    8.5000    8.8335   87.9780    2.7693    2.5748    0.2326   88.8224    4.2483   57.0000 
+2448.1250    8.5000    8.8254   85.2046    2.8487    2.5769    0.2254   88.2592    4.0521   57.0000 
+2448.2250    8.5000    8.8254   83.9638    2.9463    2.5817    0.2183   87.6847    3.9089   57.0000 
+2448.3250    8.5000    8.8008   84.0906    3.0618    2.5890    0.2138   87.0546    3.9047   57.0000 
+2448.4250    8.5000    8.8090   85.9498    3.1886    2.5990    0.2121   86.4378    4.0502   57.0000 
+2448.5250    8.5000    8.8008   88.7885    3.3161    2.6087    0.2109   85.9791    4.2042   57.0000 
+2448.6250    8.5000    8.8335   92.1151    3.4352    2.6106    0.2121   85.8260    4.2806   57.0000 
+2448.7250    8.5000    8.8335   95.1498    3.5347    2.6096    0.2161   85.9663    4.3936   57.0000 
+2448.8250    8.5000    8.8417   97.1396    3.5875    2.6024    0.2258   86.4281    4.5759   57.0000 
+2448.9250    8.5000    8.8254   98.6031    3.5489    2.5969    0.2336   87.2413    4.7235   57.0000 
+2449.0250    8.5000    8.7926  100.2588    3.3932    2.5931    0.2397   88.4209    4.8517   57.0000 
+2449.1250    8.5000    8.8172  101.9720    3.1606    2.5932    0.2400   89.9087    4.8657   57.0000 
+2449.2250    8.5000    8.8335  103.0975    2.9344    2.5961    0.2421   91.4750    4.9933   57.0000 
+2449.3250    8.5000    8.8744  102.7979    2.7701    2.5954    0.2440   92.8260    5.0410   57.0000 
+2449.4250    8.5000    8.8826  100.6006    2.6724    2.5953    0.2491   93.6418    5.2079   57.0000 
+2449.5250    8.5000    8.8254   97.8272    2.6149    2.5891    0.2524   93.8964    5.1966   57.0000 
+2449.6250    8.5000    8.8335   95.2074    2.5682    2.5835    0.2551   93.7296    5.1754   57.0000 
+2449.7250    8.5000    8.8008   93.7362    2.5201    2.5759    0.2556   93.3714    5.0375   57.0000 
+2449.8250    8.5000    8.8254   92.8565    2.4810    2.5773    0.2566   93.0194    5.0982   57.0000 
+2449.9250    8.5000    8.8417   92.6337    2.4676    2.5790    0.2589   92.7347    5.2116   57.0000 
+2450.0250    8.5000    8.8499   93.4557    2.4840    2.5831    0.2600   92.6367    5.3309   57.0000 
+2450.1250    8.5000    8.8335   94.7657    2.5162    2.5810    0.2611   92.8842    5.3240   57.0000 
+2450.2250    8.5000    8.8254   97.0589    2.5392    2.5829    0.2597   93.5791    5.3145   57.0000 
+2450.3250    8.5000    8.8254   98.0884    2.5322    2.5861    0.2588   94.7010    5.3499   57.0000 
+2450.4250    8.5000    8.8172   97.0512    2.4906    2.5923    0.2543   95.6066    5.3212   57.0000 
+2450.5250    8.5000    8.8417   94.5237    2.4300    2.5964    0.2471   95.7883    5.1652   57.0000 
+2450.6250    8.5000    8.8090   92.5146    2.3809    2.5978    0.2366   94.9816    4.8418   57.0000 
+2450.7250    8.5000    8.8008   91.8193    2.3748    2.5993    0.2263   93.2709    4.5281   57.0000 
+2450.8250    8.5000    8.7681   92.6337    2.4350    2.6007    0.2170   91.3082    4.2451   57.0000 
+2450.9250    8.5000    8.8008   94.8463    2.5751    2.6053    0.2097   89.5179    4.0974   57.0000 
+2451.0250    8.5000    8.7763   95.5608    2.7945    2.6104    0.2047   88.1403    4.0327   57.0000 
+2451.1250    8.5000    8.7926   95.3034    3.0675    2.6122    0.2022   87.2311    3.9819   57.0000 
+2451.2250    8.5000    8.8172   95.0345    3.3320    2.6063    0.2023   86.6781    3.8700   57.0000 
+2451.3250    8.5000    8.8254   93.4135    3.5173    2.5916    0.2021   86.2577    3.5699   57.0000 
+2451.4250    8.5000    8.8254   91.2931    3.6057    2.5797    0.2020   85.8000    3.3284   57.0000 
+2451.5250    8.5000    8.8008   90.6977    3.6416    2.5733    0.2005   85.1954    3.1496   57.0000 
+2451.6250    8.5000    8.7845   90.4365    3.6766    2.5774    0.1997   84.4995    3.2044   57.0000 
+2451.7250    8.5000    8.7517   90.2828    3.7254    2.5794    0.1993   83.8765    3.2296   57.0000 
+2451.8250    8.5000    8.8090   91.3968    3.7690    2.5810    0.1992   83.4714    3.2593   57.0000 
+2451.9250    8.5000    8.7926   90.3251    3.7894    2.5790    0.1986   83.2923    3.2018   57.0000 
+2452.0250    8.5000    8.8335   87.7667    3.7963    2.5812    0.1964   83.1510    3.1709   57.0000 
+2452.1250    8.5000    8.8417   86.1457    3.8166    2.5824    0.1950   83.2168    3.1497   57.0000 
+2452.2250    8.5000    8.8172   85.1815    3.8801    2.5810    0.1948   83.4316    3.1147   57.0000 
+2452.3250    8.5000    8.8090   86.1034    4.0105    2.5756    0.1985   84.0444    3.1283   57.0000 
+2452.4250    8.5000    8.8090   88.6695    4.2234    2.5691    0.2038   85.1235    3.1756   57.0000 
+2452.5250    8.5000    8.8090   91.4506    4.5115    2.5670    0.2107   86.2352    3.3630   57.0000 
+2452.6250    8.5000    8.8417   93.2944    4.7852    2.5665    0.2155   87.3704    3.5155   57.0000 
+2452.7250    8.5000    8.8254   94.5659    4.8518    2.5716    0.2186   88.1082    3.7180   57.0000 
+2452.8250    8.5000    8.8172   94.4430    4.6275    2.5752    0.2187   88.2209    3.7936   57.0000 
+2452.9250    8.5000    8.7926   93.6593    4.3146    2.5820    0.2177   87.7908    3.8965   57.0000 
+2453.0250    8.5000    8.7845   92.4109    4.1131    2.5850    0.2147   86.8214    3.8552   57.0000 
+2453.1250    8.5000    8.7845   90.1906    4.0426    2.5899    0.2112   85.7985    3.8398   57.0000 
+2453.2250    8.5000    8.8090   88.9115    4.0255    2.5956    0.2059   85.1051    3.7769   57.0000 
+2453.3250    8.5000    8.8581   87.4095    4.0033    2.6030    0.2007   84.5663    3.7491   57.0000 
+2453.4250    8.5000    8.8499   86.7257    3.9753    2.6070    0.1933   84.0138    3.5836   57.0000 
+2453.5250    8.5000    8.8417   87.0830    4.0023    2.6023    0.1864   83.2347    3.2572   57.0000 
+2453.6250    8.5000    8.8090   88.3122    4.1560    2.5919    0.1789   82.3582    2.8013   57.0000 
+2453.7250    8.5000    8.8090   91.3891    4.4592    2.5809    0.1753   81.7230    2.4623   57.0000 
+2453.8250    8.5000    8.8335   93.7746    4.8599    2.5746    0.1748   81.4051    2.3177   57.0000 
+2453.9250    8.5000    8.8254   96.4174    5.2413    2.5760    0.1781   81.3306    2.4546   57.0000 
+2454.0250    8.5000    8.8254   97.5084    5.4855    2.5825    0.1814   81.2827    2.6960   57.0000 
+2454.1250    8.5000    8.8172   95.9373    5.5276    2.5913    0.1853   81.2959    3.0035   57.0000 
+2454.2250    8.5000    8.7926   94.9308    5.3876    2.5972    0.1897   81.4628    3.2660   57.0000 
+2454.3250    8.5000    8.8172   93.3828    5.1403    2.6021    0.1946   81.7801    3.5305   57.0000 
+2454.4250    8.5000    8.8254   91.9192    4.8762    2.6022    0.1971   82.0878    3.6129   57.0000 
+2454.5250    8.5000    8.8663   92.2227    4.6726    2.5961    0.1947   82.0418    3.4116   57.0000 
+2454.6250    8.5000    8.8908   92.0613    4.5854    2.5835    0.1882   81.4112    2.9429   57.0000 
+2454.7250    8.5000    8.8826   92.5031    4.6456    2.5772    0.1814   80.2051    2.5901   57.0000 
+2454.8250    8.5000    8.8744   92.4416    4.8587    2.5839    0.1771   78.5867    2.5815   57.0000 
+2454.9250    8.5000    8.8335   90.3788    5.1962    2.5952    0.1754   77.0541    2.7513   57.0000 
+2455.0250    8.5000    8.8172   88.1432    5.5706    2.5992    0.1748   76.0010    2.8109   57.0000 
+2455.1250    8.5000    8.8172   84.1943    5.8477    2.5897    0.1730   75.8541    2.5628   57.0000 
+2455.2250    8.5000    8.8581   82.1930    5.9518    2.5839    0.1712   76.4755    2.3845   57.0000 
+2455.3250    8.5000    8.8908   84.2750    5.9403    2.5869    0.1695   77.5291    2.3877   57.0000 
+2455.4250    8.5000    8.8826   88.4697    5.9242    2.6007    0.1713   78.1974    2.7228   57.0000 
+2455.5250    8.5000    8.8908   93.7669    5.9365    2.6085    0.1763   78.3388    3.0481   57.0000 
+2455.6250    8.5000    8.8335   97.4930    5.9038    2.6075    0.1841   78.1643    3.2869   57.0000 
+2455.7250    8.5000    8.8254   97.9348    5.7435    2.5983    0.1903   78.0975    3.3077   57.0000 
+2455.8250    8.5000    8.8254   95.5070    5.4723    2.5880    0.1935   78.5260    3.2093   57.0000 
+2455.9250    8.5000    8.8254   93.0025    5.1793    2.5790    0.1927   79.2755    3.0027   57.0000 
+2456.0250    8.5000    8.8663   90.2060    4.9540    2.5717    0.1897   79.9638    2.7575   57.0000 
+2456.1250    8.5000    8.8581   86.8563    4.8515    2.5674    0.1838   80.3112    2.4742   57.0000 
+2456.2250    8.5000    8.8826   84.5439    4.8895    2.5673    0.1788   79.9760    2.3050   57.0000 
+2456.3250    8.5000    8.8826   83.2071    5.0543    2.5730    0.1749   79.2383    2.2901   57.0000 
+2456.4250    8.5000    8.8908   83.0995    5.3158    2.5796    0.1742   78.2735    2.3996   57.0000 
+2456.5250    8.5000    8.9235   84.5592    5.6216    2.5821    0.1731   77.6459    2.4100   57.0000 
+2456.6250    8.5000    8.9317   86.3186    5.8923    2.5770    0.1731   77.3770    2.3091   57.0000 
+2456.7250    8.5000    8.9153   86.1841    6.0361    2.5728    0.1743   77.4321    2.2663   57.0000 
+2456.8250    8.5000    8.8990   84.0714    6.0027    2.5742    0.1769   77.6878    2.3817   57.0000 
+2456.9250    8.5000    8.9235   79.6462    5.8421    2.5750    0.1762   77.8786    2.3748   57.0000 
+2457.0250    8.5000    8.9235   73.2235    5.6860    2.5708    0.1682   77.8316    2.0248   57.0000 
+2457.1250    8.5000    8.9399   65.8865    5.6615    2.5578    0.1536   77.4082    1.2751   57.0000 
+2457.2250    8.5000    8.9562   59.6789    5.8417    2.5513    0.1361   76.6071    0.5623   57.0000 
+2457.3250    8.5000    8.9562   54.7006    6.2789    2.5483    0.1223   75.6173    0.0422   54.0000 
+2457.4250    8.5000    8.9317   51.7197    7.0326    2.5519    0.1133   74.5816   -0.1843   54.0000 
+2457.5250    8.5000    8.9317   50.6134    8.1418    2.5489    0.1076   73.5510   -0.4342   25.0000 
+2457.6250    8.5000    8.9317   49.5724    9.5558    2.5447    0.0999   72.5612   -0.7772   25.0000 
+2457.7250    8.5000    8.9317   49.7260   11.0988    2.5405    0.0904   71.5204   -1.1753   49.0000 
+2457.8250    8.5000    8.9399   49.5801   12.6082    2.5426    0.0820   70.4235   -1.4163   49.0000 
+2457.9250    8.5000    8.9235   50.4559   14.0867    2.5457    0.0796   69.1990   -1.4326   49.0000 
+2458.0250    8.5000    8.9317   52.2920   15.6862    2.5486    0.0835   67.8673   -1.2452   49.0000 
+2458.1250    8.5000    8.9153   54.2742   17.4138    2.5526    0.0921   66.6888   -0.8778   25.0000 
+2458.2250    8.5000    8.9153   56.7634   18.8877    2.5597    0.1016   65.8163   -0.4172   25.0000 
+2458.3250    8.5000    8.8581   58.5304   19.2484    2.5683    0.1114   65.5153    0.0790   54.0000 
+2458.4250    8.5000    8.8335   59.6482   18.2389    2.5714    0.1205   65.9102    0.4424   57.0000 
+2458.5250    8.5000    8.8090   60.1092   16.2177    2.5662    0.1285   67.0842    0.6076   57.0000 
+2458.6250    8.5000    8.8172   61.7148   13.9748    2.5577    0.1357   68.6046    0.6779   57.0000 
+2458.7250    8.5000    8.8499   65.2104   12.0224    2.5513    0.1439   70.1872    0.8229   57.0000 
+2458.8250    8.5000    8.8581   69.6049   10.4662    2.5522    0.1552   71.4903    1.2178   57.0000 
+2458.9250    8.5000    8.8826   73.8842    9.2187    2.5524    0.1680   72.3648    1.6489   57.0000 
+2459.0250    8.5000    8.8417   77.3951    8.1110    2.5542    0.1790   73.2087    2.0518   57.0000 
+2459.1250    8.5000    8.8581   79.2236    7.0581    2.5588    0.1872   73.9117    2.4150   57.0000 
+2459.2250    8.5000    8.8335   82.4964    6.0908    2.5718    0.1931   74.7225    2.8725   57.0000 
+2459.3250    8.5000    8.8499   88.9652    5.3449    2.5866    0.1999   75.6255    3.3938   57.0000 
+2459.4250    8.5000    8.8990   95.1805    4.8537    2.5968    0.2066   76.6689    3.8227   57.0000 
+2459.5250    8.5000    8.8908  101.1499    4.5394    2.5993    0.2138   78.1821    4.1124   57.0000 
+2459.6250    8.5000    8.9235  103.9695    4.2785    2.5936    0.2207   80.0883    4.2279   57.0000 
+2459.7250    8.5000    8.9072  101.8260    3.9709    2.5875    0.2278   82.1168    4.3452   57.0000 
+2459.8250    8.5000    8.8663   97.9232    3.6129    2.5803    0.2328   83.8954    4.3657   57.0000 
+2459.9250    8.5000    8.8908   92.6836    3.2834    2.5798    0.2327   84.8602    4.3519   57.0000 
+2460.0250    8.5000    8.8826   87.6285    3.0692    2.5806    0.2258   85.1653    4.1386   57.0000 
+2460.1250    8.5000    8.8990   84.0406    3.0206    2.5866    0.2147   84.9526    3.8903   57.0000 
+2460.2250    8.5000    8.9153   80.5604    3.1541    2.5929    0.2028   84.4679    3.6196   57.0000 
+2460.3250    8.5000    8.9235   75.4514    3.4431    2.5969    0.1910   83.9148    3.3025   57.0000 
+2460.4250    8.5000    8.9072   68.3450    3.7832    2.5995    0.1761   83.0969    2.8615   57.0000 
+2460.5250    8.5000    8.8744   59.6136    4.0179    2.5985    0.1542   81.8964    2.1101   57.0000 
+2460.6250    8.5000    8.8581   50.5212    4.0914    2.5969    0.1261   80.0602    1.1427   57.0000 
+2460.7250    8.5000    8.8663   44.2445    4.1210    2.5922    0.1003   77.4378    0.1870   54.0000 
+2460.8250    8.5000    8.8744   40.7488    4.2836    2.5864    0.0883   74.2633   -0.3301   25.0000 
+2460.9250    8.5000    8.9235   41.9089    4.6761    2.5808    0.0965   71.0107   -0.1663   54.0000 
+2461.0250    8.5000    8.9317   48.3816    5.3558    2.5727    0.1224   68.4699    0.5359   57.0000 
+2461.1250    8.5000    8.8908   58.3767    6.1875    2.5642    0.1555   67.0918    1.4657   57.0000 
+2461.2250    8.5000    8.9072   72.6204    6.8862    2.5530    0.1834   67.4036    2.1727   57.0000 
+2461.3250    8.5000    8.9153   85.7232    7.0200    2.5425    0.2008   69.8230    2.5440   57.0000 
+2461.4250    8.5000    8.9399   95.1075    6.5875    2.5350    0.2087   73.6485    2.6583   57.0000 
+2461.5250    8.5000    8.9399  100.8772    5.8152    2.5296    0.2128   77.7571    2.6869   57.0000 
+2461.6250    8.5000    8.9153  100.0782    5.1641    2.5278    0.2120   80.3056    2.6236   57.0000 
+2461.7250    8.5000    8.8826   96.2599    4.7742    2.5252    0.2074   80.7347    2.4175   57.0000 
+2461.8250    8.5000    8.8744   92.7067    4.6545    2.5255    0.1991   79.9607    2.1485   57.0000 
+2461.9250    8.5000    8.8744   89.3571    4.8113    2.5305    0.1971   78.6781    2.1819   57.0000 
+2462.0250    8.5000    8.8663   88.5427    5.2547    2.5389    0.2016   77.6352    2.4972   57.0000 
+2462.1250    8.5000    8.8990   90.6669    5.9171    2.5536    0.2119   76.5526    3.1364   57.0000 
+2462.2250    8.5000    8.9235   92.3110    6.5440    2.5644    0.2190   75.6250    3.5890   57.0000 
+2462.3250    8.5000    8.9481   94.4468    6.7651    2.5745    0.2222   75.5250    3.8965   57.0000 
+2462.4250    8.5000    8.9808   97.2587    6.4849    2.5777    0.2213   76.6653    3.9300   57.0000 
+2462.5250    8.5000    8.9644   98.0961    5.9662    2.5755    0.2184   78.8898    3.7895   57.0000 
+2462.6250    8.5000    8.9644   98.7683    5.4814    2.5691    0.2138   81.5704    3.5085   57.0000 
+2462.7250    8.5000    8.9890   97.8771    5.1250    2.5596    0.2083   83.5964    3.1345   57.0000 
+2462.8250    8.5000    9.0299   95.5723    4.8876    2.5553    0.2031   84.8750    2.8778   57.0000 
+2462.9250    8.5000    9.0544   94.5928    4.7485    2.5541    0.1999   85.3475    2.7467   57.0000 
+2463.0250    8.5000    9.0626   94.1241    4.7132    2.5541    0.2005   85.4872    2.7663   57.0000 
+2463.1250    8.5000    9.0380   94.9692    4.7957    2.5557    0.2034   85.3862    2.8946   57.0000 
+2463.2250    8.5000    9.0135   94.8617    4.9822    2.5602    0.2069   84.8143    3.0986   57.0000 
+2463.3250    8.5000    9.0135   93.1100    5.2047    2.5729    0.2073   83.9878    3.3682   57.0000 
+2463.4250    8.5000    9.0217   90.9090    5.3483    2.5866    0.2070   83.1026    3.6339   57.0000 
+2463.5250    8.5000    9.0299   87.4518    5.3388    2.5965    0.2061   82.3041    3.7986   57.0000 
+2463.6250    8.5000    9.0462   85.3698    5.2250    2.5958    0.2044   81.5653    3.7278   57.0000 
+2463.7250    8.5000    9.0380   83.9408    5.1292    2.5929    0.1992   80.6730    3.4994   57.0000 
+2463.8250    8.5000    9.0299   82.3620    5.1439    2.5978    0.1929   79.6168    3.3854   57.0000 
+2463.9250    8.5000    9.0217   83.2839    5.2925    2.6142    0.1880   78.6862    3.5491   57.0000 
+2464.0250    8.5000    9.0299   86.3954    5.5394    2.6273    0.1877   77.8781    3.8030   57.0000 
+2464.1250    8.5000    9.0462   91.5735    5.8054    2.6244    0.1887   77.3046    3.7772   57.0000 
+2464.2250    8.5000    9.0544   97.3278    5.9931    2.6082    0.1895   77.0520    3.4785   57.0000 
+2464.3250    8.5000    9.0544  100.2319    6.0388    2.5907    0.1855   76.7832    2.9984   57.0000 
+2464.4250    8.5000    9.0299  100.2703    5.9638    2.5854    0.1798   76.5214    2.6996   57.0000 
+2464.5250    8.5000    9.0135   98.4572    5.8575    2.5866    0.1723   75.9480    2.4755   57.0000 
+2464.6250    8.5000    9.0053   96.8784    5.8043    2.5939    0.1676   75.3020    2.4636   57.0000 
+2464.7250    8.5000    8.9971   96.8169    5.8519    2.5967    0.1665   74.6673    2.4860   57.0000 
+2464.8250    8.5000    9.0217   97.2779    5.9980    2.5991    0.1711   74.2490    2.6836   57.0000 
+2464.9250    8.5000    9.0462   97.2318    6.1876    2.5961    0.1799   74.1643    2.9202   57.0000 
+2465.0250    8.5000    9.0380   97.7696    6.2964    2.5950    0.1891   74.5031    3.2026   57.0000 
+2465.1250    8.5000    9.0217   99.3445    6.2284    2.5888    0.1958   75.1878    3.3012   57.0000 
+2465.2250    8.5000    8.9890  101.0693    5.9997    2.5857    0.1981   75.9745    3.3164   57.0000 
+2465.3250    8.5000    8.9890  104.0194    5.7035    2.5811    0.1999   76.8622    3.2844   57.0000 
+2465.4250    8.5000    8.9890  106.5547    5.4074    2.5861    0.2029   77.8367    3.4838   57.0000 
+2465.5250    8.5000    8.9971  106.5470    5.1370    2.5890    0.2075   79.2245    3.6959   57.0000 
+2465.6250    8.5000    8.9971  104.5111    4.9053    2.5918    0.2080   80.8469    3.7693   57.0000 
+2465.7250    8.5000    8.9971   99.0872    4.7262    2.5897    0.2013   82.3061    3.5062   57.0000 
+2465.8250    8.5000    9.0053   90.0062    4.6240    2.5929    0.1881   83.3673    3.1272   57.0000 
+2465.9250    8.5000    9.0135   80.7755    4.6366    2.5921    0.1734   83.5714    2.6217   57.0000 
+2466.0250    8.5000    9.0135   72.1210    4.8285    2.5876    0.1582   82.9745    2.0252   57.0000 
+2466.1250    8.5000    9.0217   65.5754    5.2937    2.5779    0.1423   81.4133    1.3015   57.0000 
+2466.2250    8.5000    9.0708   61.5804    6.1305    2.5757    0.1248   78.9949    0.6759   57.0000 
+2466.3250    8.5000    9.0871   58.1078    7.3734    2.5781    0.1085   76.1225    0.1784   54.0000 
+2466.4250    8.5000    9.0789   56.8786    8.8663    2.5803    0.0968   73.3622   -0.1676   54.0000 
+2466.5250    8.5000    9.1035   56.7710   10.3591    2.5830    0.0921   71.2959   -0.2692   54.0000 
+2466.6250    8.5000    9.0789   56.8018   11.5470    2.5857    0.0946   70.0867   -0.1339   54.0000 
+2466.7250    8.5000    9.1035   57.5278   12.3394    2.5873    0.0995   69.5714    0.0625   54.0000 
+2466.8250    8.5000    9.1280   56.8555   12.7914    2.5758    0.1036   69.4184   -0.0291   54.0000 
+2466.9250    8.5000    9.1198   55.7953   12.9270    2.5586    0.1062   69.4490   -0.2893   54.0000 
+2467.0250    8.5000    9.1035   56.6212   12.8520    2.5446    0.1100   69.6071   -0.4420   25.0000 
+2467.1250    8.5000    9.1035   59.6943   12.5557    2.5447    0.1165   69.9235   -0.2233   54.0000 
+2467.2250    8.5000    9.1444   65.1567   12.0539    2.5569    0.1276   70.6173    0.3939   57.0000 
+2467.3250    8.5000    9.1117   71.0570   11.3552    2.5709    0.1431   71.6480    1.1890   57.0000 
+2467.4250    8.5000    9.1444   76.6576   10.5186    2.5820    0.1612   73.0510    2.0140   57.0000 
+2467.5250    8.5000    9.1362   79.9074    9.5113    2.5832    0.1765   74.5918    2.5481   57.0000 
+2467.6250    8.5000    9.1280   81.7973    8.4892    2.5876    0.1833   76.0918    2.8630   57.0000 
+2467.7250    8.5000    9.1117   83.2570    7.5729    2.5900    0.1804   77.3571    2.8149   57.0000 
+2467.8250    8.5000    9.1035   82.0316    6.8412    2.5932    0.1706   78.1990    2.5493   57.0000 
+2467.9250    8.5000    9.1280   80.1571    6.3352    2.5860    0.1596   78.8929    2.0384   57.0000 
+2468.0250    8.5000    9.1444   76.6461    6.0580    2.5776    0.1506   79.5153    1.5738   57.0000 
+2468.1250    8.5000    9.1444   71.5525    6.0070    2.5711    0.1431   80.0408    1.1905   57.0000 
+2468.2250    8.5000    9.1771   68.8328    6.1682    2.5687    0.1373   80.4235    0.9489   57.0000 
+2468.3250    8.5000    9.1689   67.9570    6.5104    2.5673    0.1332   79.9025    0.7858   57.0000 
+2468.4250    8.5000    9.1525   69.1747    6.9827    2.5655    0.1335   78.5791    0.7611   57.0000 
+2468.5250    8.5000    9.1444   74.6448    7.5241    2.5679    0.1360   76.7679    0.8906   57.0000 
+2468.6250    8.5000    9.1117   80.6295    8.0503    2.5702    0.1416   75.0179    1.1247   57.0000 
+2468.7250    8.5000    9.0871   86.2609    8.4519    2.5739    0.1480   73.9561    1.4138   57.0000 
+2468.8250    8.5000    9.0953   90.3404    8.6153    2.5711    0.1559   73.7066    1.6198   57.0000 
+2468.9250    8.5000    9.0953   90.1330    8.4805    2.5734    0.1607   73.9985    1.8243   57.0000 
+2469.0250    8.5000    9.1198   87.1752    8.1024    2.5764    0.1620   74.3786    1.9283   57.0000 
+2469.1250    8.5000    9.1362   82.8729    7.6213    2.5852    0.1616   74.4020    2.0926   57.0000 
+2469.2250    8.5000    9.1280   80.3683    7.1853    2.5903    0.1637   73.8337    2.2627   57.0000 
+2469.3250    8.5000    9.1362   81.3364    6.8883    2.6066    0.1704   73.0112    2.8107   57.0000 
+2469.4250    8.5000    9.1280   84.9126    6.7912    2.6280    0.1800   72.2199    3.5592   57.0000 
+2469.5250    8.5000    9.1362   90.2521    6.9196    2.6450    0.1926   72.2750    4.3186   57.0000 
+2469.6250    8.5000    9.1444   95.4379    7.2468    2.6353    0.2069   73.5117    4.6006   57.0000 
+2469.7250    8.5000    9.1198   99.4367    7.6452    2.6081    0.2225   75.9230    4.5787   57.0000 
+2469.8250    8.5000    9.1198  103.2166    7.8640    2.5862    0.2363   79.1893    4.6002   57.0000 
+2469.9250    8.5000    9.1035  107.0157    7.6764    2.5830    0.2482   82.5301    4.9326   57.0000 
+2470.0250    8.5000    9.0871  109.5048    7.0141    2.5951    0.2583   85.6199    5.5112   57.0000 
+2470.1250    8.5000    9.0953  110.4729    6.1600    2.6043    0.2671   88.2577    5.9868   57.0000 
+2470.2250    8.5000    9.0871  109.5548    5.3469    2.6046    0.2715   90.3010    6.1417   57.0000 
+2470.3250    8.5000    9.0708  107.9337    4.6767    2.6016    0.2718   91.8184    6.0919   57.0000 
+2470.4250    8.5000    9.0953  106.4740    4.1731    2.5992    0.2685   93.0959    5.9341   57.0000 
+2470.5250    8.5000    9.1035  106.1245    3.8278    2.6007    0.2651   94.2571    5.8516   57.0000 
+2470.6250    8.5000    9.1035  107.3230    3.6096    2.5973    0.2615   95.4296    5.6608   57.0000 
+2470.7250    8.5000    9.0789  107.8147    3.4819    2.5990    0.2591   96.3296    5.6156   57.0000 
+2470.8250    8.5000    9.0953  108.2449    3.4109    2.6021    0.2596   96.5485    5.6942   57.0000 
+2470.9250    8.5000    9.1035  107.8070    3.3696    2.6084    0.2602   96.3714    5.8418   57.0000 
+2471.0250    8.5000    9.1280  106.4702    3.3421    2.6098    0.2577   95.9219    5.7852   57.0000 
+2471.1250    8.5000    9.1444  105.1680    3.3245    2.6078    0.2485   95.2378    5.4383   57.0000 
+2471.2250    8.5000    9.1362  104.2768    3.3234    2.6034    0.2381   93.9265    5.0056   57.0000 
+2471.3250    8.5000    9.1280  103.2012    3.3564    2.6010    0.2303   91.6148    4.6964   57.0000 
+2471.4250    8.5000    9.1362  101.8260    3.4383    2.6053    0.2254   88.6648    4.6196   57.0000 
+2471.5250    8.5000    9.1198  100.2933    3.5652    2.6147    0.2187   85.5786    4.5836   57.0000 
+2471.6250    8.5000    9.1280   98.7491    3.7236    2.6182    0.2103   83.0546    4.3753   57.0000 
+2471.7250    8.5000    9.1117   98.2613    3.9095    2.6127    0.2023   81.7475    3.9964   57.0000 
+2471.8250    8.5000    9.1035   98.9757    4.1500    2.5999    0.2002   81.7684    3.6709   57.0000 
+2471.9250    8.5000    9.1035  101.9681    4.5128    2.5900    0.2022   83.2311    3.5383   57.0000 
+2472.0250    8.5000    9.1117  105.1641    5.0684    2.5834    0.2097   85.6724    3.6571   57.0000 
+2472.1250    8.5000    9.1280  108.4869    5.7366    2.5814    0.2181   88.4888    3.8993   57.0000 
+2472.2250    8.5000    9.1280  111.0759    5.9804    2.5787    0.2311   91.2199    4.2774   57.0000 
+2472.3250    8.5000    9.1689  110.5535    5.4096    2.5724    0.2435   93.2525    4.5636   57.0000 
+2472.4250    8.5000    9.1362  108.7289    4.4147    2.5633    0.2543   94.4296    4.7435   57.0000 
+2472.5250    8.5000    9.1280  106.2320    3.5841    2.5614    0.2578   94.7546    4.8202   57.0000 
+2472.6250    8.5000    9.1362  103.0821    3.1051    2.5701    0.2566   94.3949    4.9563   57.0000 
+2472.7250    8.5000    9.1117  101.7722    2.8778    2.5857    0.2549   93.8367    5.2100   57.0000 
+2472.8250    8.5000    9.1362  100.8273    2.7911    2.5943    0.2552   93.3561    5.3919   57.0000 
+2472.9250    8.5000    9.1771   98.5993    2.7692    2.5972    0.2576   93.0480    5.5311   57.0000 
+2473.0250    8.5000    9.1771   97.1550    2.7679    2.5899    0.2585   92.9107    5.4130   57.0000 
+2473.1250    8.5000    9.2262   94.2740    2.7706    2.5828    0.2588   92.7709    5.2809   57.0000 
+2473.2250    8.5000    9.2507   92.4916    2.7764    2.5760    0.2588   92.6612    5.1477   57.0000 
+2473.3250    8.5000    9.2589   92.6491    2.7890    2.5786    0.2584   92.5827    5.1853   57.0000 
+2473.4250    8.5000    9.2180   92.5031    2.8087    2.5852    0.2555   92.5158    5.2209   57.0000 
+2473.5250    8.5000    9.1934   93.7746    2.8316    2.5861    0.2520   92.5439    5.1201   57.0000 
+2473.6250    8.5000    9.1771   94.0320    2.8539    2.5844    0.2502   92.5122    5.0283   57.0000 
+2473.7250    8.5000    9.1689   93.8207    2.8742    2.5765    0.2525   92.5230    4.9461   57.0000 
+2473.8250    8.5000    9.1853   94.2048    2.8926    2.5722    0.2574   92.5923    5.0231   57.0000 
+2473.9250    8.5000    9.2016   94.2932    2.9088    2.5653    0.2647   92.7464    5.1293   57.0000 
+2474.0250    8.5000    9.2507   95.0998    2.9212    2.5633    0.2723   93.0755    5.3431   57.0000 
+2474.1250    8.5000    9.2180   96.7439    2.9295    2.5665    0.2753   93.3097    5.5050   57.0000 
+2474.2250    8.5000    9.1934   98.5494    2.9421    2.5774    0.2723   93.3653    5.6247   57.0000 
+2474.3250    8.5000    9.1607  100.3932    2.9755    2.5939    0.2660   93.1301    5.7469   57.0000 
+2474.4250    8.5000    9.1362  102.6826    3.0478    2.6049    0.2615   92.6138    5.8156   57.0000 
+2474.5250    8.5000    9.1771  103.9656    3.1637    2.5986    0.2618   92.1107    5.6971   57.0000 
+2474.6250    8.5000    9.2098  103.5392    3.3020    2.5770    0.2637   91.6209    5.3294   57.0000 
+2474.7250    8.5000    9.2343  102.1295    3.4253    2.5547    0.2664   91.6092    4.9750   57.0000 
+2474.8250    8.5000    9.2752   99.8746    3.5058    2.5434    0.2667   91.9337    4.7588   57.0000 
+2474.9250    8.5000    9.2507   96.5557    3.5346    2.5406    0.2664   92.4837    4.6913   57.0000 
+2475.0250    8.5000    9.2507   95.4110    3.5175    2.5403    0.2660   93.0827    4.6724   57.0000 
+2475.1250    8.5000    9.2262   96.7247    3.4707    2.5446    0.2657   93.4571    4.7492   57.0000 
+2475.2250    8.5000    9.2343   97.5199    3.4209    2.5528    0.2652   94.0092    4.8972   57.0000 
+2475.3250    8.5000    9.2507  100.4393    3.3950    2.5619    0.2627   94.6724    4.9937   57.0000 
+2475.4250    8.5000    9.2671  102.9016    3.4054    2.5667    0.2602   95.5546    5.0074   57.0000 
+2475.5250    8.5000    9.2752  102.7556    3.4390    2.5677    0.2585   96.1709    4.9721   57.0000 
+2475.6250    8.5000    9.2834  103.4317    3.4678    2.5696    0.2602   96.2179    5.0656   57.0000 
+2475.7250    8.5000    9.2916  103.0937    3.4682    2.5769    0.2623   95.4582    5.2798   57.0000 
+2475.8250    8.5000    9.2752  100.9041    3.4327    2.5815    0.2633   93.6724    5.4072   57.0000 
+2475.9250    8.5000    9.2589   99.0603    3.3701    2.5847    0.2612   91.2061    5.3984   57.0000 
+2476.0250    8.5000    9.2343   96.8630    3.3083    2.5773    0.2599   88.6367    5.2074   57.0000 
+2476.1250    8.5000    9.2262   95.3419    3.2915    2.5742    0.2593   86.6046    5.1275   57.0000 
+2476.2250    8.5000    9.2507   95.7721    3.3549    2.5681    0.2610   85.2026    5.0632   57.0000 
+2476.3250    8.5000    9.2262   97.3893    3.5067    2.5653    0.2625   84.4837    5.0562   57.0000 
+2476.4250    8.5000    9.2507   99.0026    3.7209    2.5608    0.2656   84.0301    5.0696   57.0000 
+2476.5250    8.5000    9.2425   99.5404    3.9354    2.5637    0.2684   84.2168    5.2190   57.0000 
+2476.6250    8.5000    9.2262   99.7901    4.0720    2.5715    0.2704   84.8673    5.4426   57.0000 
+2476.7250    8.5000    9.2425   98.1537    4.0947    2.5747    0.2687   85.4995    5.4508   57.0000 
+2476.8250    8.5000    9.2262   96.7708    4.0429    2.5683    0.2645   85.4862    5.1837   57.0000 
+2476.9250    8.5000    9.1771   94.6504    3.9961    2.5621    0.2575   84.3929    4.8254   57.0000 
+2477.0250    8.5000    9.1362   90.3981    4.0172    2.5673    0.2485   82.3577    4.6275   57.0000 
+2477.1250    8.5000    9.0708   87.3442    4.1340    2.5813    0.2357   79.9015    4.4822   57.0000 
+2477.2250    8.5000    9.0626   84.8704    4.3376    2.5847    0.2215   77.2872    4.0756   57.0000 
+2477.3250    8.5000    9.0708   84.4939    4.5827    2.5767    0.2114   74.7276    3.5820   57.0000 
+2477.4250    8.5000    9.0953   86.1265    4.8125    2.5591    0.2090   72.7821    3.1495   57.0000 
+2477.5250    8.5000    9.1117   87.5094    5.0069    2.5506    0.2122   71.7138    3.0851   57.0000 
+2477.6250    8.5000    9.1035   87.5094    5.1948    2.5523    0.2132   71.6138    3.1532   57.0000 
+2477.7250    8.5000    9.1280   86.9485    5.4018    2.5680    0.2099   72.4260    3.3551   57.0000 
+2477.8250    8.5000    9.1198   87.1137    5.6002    2.5886    0.2045   73.7112    3.5904   57.0000 
+2477.9250    8.5000    9.1444   89.4531    5.7009    2.6061    0.2057   74.9046    3.9769   57.0000 
+2478.0250    8.5000    9.1607   92.9103    5.6101    2.6126    0.2160   76.3097    4.4529   57.0000 
+2478.1250    8.5000    9.1525   96.0832    5.3207    2.6024    0.2346   77.3663    4.8672   57.0000 
+2478.2250    8.5000    9.1525   98.4649    4.9249    2.5859    0.2514   79.6225    5.0969   57.0000 
+2478.3250    8.5000    9.1444   98.8567    4.5205    2.5706    0.2639   82.8571    5.2073   57.0000 
+2478.4250    8.5000    9.1362   98.9258    4.1617    2.5654    0.2693   86.6408    5.2846   57.0000 
+2478.5250    8.5000    9.1525   98.9181    3.8704    2.5603    0.2738   90.0418    5.3320   57.0000 
+2478.6250    8.5000    9.1771   99.2907    3.6590    2.5527    0.2737   92.2719    5.1766   57.0000 
+2478.7250    8.5000    9.1934   99.3099    3.5326    2.5427    0.2691   93.4597    4.8238   57.0000 
+2478.8250    8.5000    9.2016   99.1563    3.4877    2.5392    0.2564   93.4867    4.3304   57.0000 
+2478.9250    8.5000    9.2016   98.0807    3.5199    2.5463    0.2395   92.5622    3.9078   57.0000 
+2479.0250    8.5000    9.1853   94.3047    3.6348    2.5587    0.2226   90.7949    3.5928   57.0000 
+2479.1250    8.5000    9.1853   89.9717    3.8459    2.5676    0.2083   88.4378    3.2951   57.0000 
+2479.2250    8.5000    9.1771   83.9024    4.1664    2.5697    0.1980   85.9847    2.9921   57.0000 
+2479.3250    8.5000    9.2016   79.7998    4.5865    2.5721    0.1889   83.7755    2.7392   57.0000 
+2479.4250    8.5000    9.2098   78.8280    5.0354    2.5811    0.1824   82.1694    2.7007   57.0000 
+2479.5250    8.5000    9.2589   78.6820    5.3665    2.5949    0.1769   81.2245    2.7929   57.0000 
+2479.6250    8.5000    9.2589   80.9253    5.4455    2.6059    0.1749   80.9327    2.9472   57.0000 
+2479.7250    8.5000    9.2834   80.5105    5.2884    2.6110    0.1755   80.8781    3.0703   57.0000 
+2479.8250    8.5000    9.3325   78.6167    5.0353    2.6101    0.1768   81.1199    3.0963   57.0000 
+2479.9250    8.5000    9.3489   76.6730    4.8163    2.6062    0.1777   81.5250    3.0462   57.0000 
+2480.0250    8.5000    9.3570   74.7984    4.6918    2.5973    0.1779   82.0577    2.8743   57.0000 
+2480.1250    8.5000    9.3407   76.8266    4.6625    2.5909    0.1824   82.5923    2.8974   57.0000 
+2480.2250    8.5000    9.3325   80.7179    4.6863    2.5859    0.1911   82.9352    3.0865   57.0000 
+2480.3250    8.5000    9.3080   86.6566    4.6991    2.5883    0.2047   83.1872    3.5868   57.0000 
+2480.4250    8.5000    9.3080   93.5134    4.6589    2.5881    0.2194   83.8260    4.0748   57.0000 
+2480.5250    8.5000    9.2916   97.2625    4.5688    2.5875    0.2324   85.3423    4.4942   57.0000 
+2480.6250    8.5000    9.3080   99.5135    4.4450    2.5786    0.2403   87.7010    4.5818   57.0000 
+2480.7250    8.5000    9.3325  100.3279    4.2888    2.5628    0.2434   90.4571    4.3699   57.0000 
+2480.8250    8.5000    9.3407   99.0987    4.0976    2.5472    0.2445   92.8418    4.0946   57.0000 
+2480.9250    8.5000    9.3407   99.2024    3.8826    2.5426    0.2439   94.5485    3.9838   57.0000 
+2481.0250    8.5000    9.3325   98.9719    3.6635    2.5506    0.2440   95.4791    4.1466   57.0000 
+2481.1250    8.5000    9.3570   97.9732    3.4583    2.5587    0.2444   95.5311    4.3221   57.0000 
+2481.2250    8.5000    9.3243   97.1165    3.2902    2.5602    0.2458   94.7709    4.3980   57.0000 
+2481.3250    8.5000    9.3325   95.2804    3.1894    2.5589    0.2419   93.1179    4.2418   57.0000 
+2481.4250    8.5000    9.3570   93.9743    3.1785    2.5640    0.2322   91.0668    4.0205   57.0000 
+2481.5250    8.5000    9.3325   93.5825    3.2696    2.5705    0.2190   89.0485    3.7105   57.0000 
+2481.6250    8.5000    9.2998   93.6824    3.4623    2.5811    0.2083   87.5265    3.5671   57.0000 
+2481.7250    8.5000    9.2671   94.2163    3.7255    2.5879    0.2026   86.4821    3.5097   57.0000 
+2481.8250    8.5000    9.2752   94.6312    3.9912    2.5996    0.2047   85.8036    3.8149   57.0000 
+2481.9250    8.5000    9.3161   93.8015    4.1847    2.6009    0.2137   85.5806    4.1433   57.0000 
+2482.0250    8.5000    9.3243   92.5991    4.2647    2.5960    0.2271   85.9408    4.4899   57.0000 
+2482.1250    8.5000    9.3325   92.5223    4.2293    2.5781    0.2406   87.0735    4.5816   57.0000 
+2482.2250    8.5000    9.3489   92.9679    4.1028    2.5604    0.2527   88.6847    4.6331   57.0000 
+2482.3250    8.5000    9.3570   94.7887    3.9295    2.5437    0.2633   90.4204    4.6493   57.0000 
+2482.4250    8.5000    9.3979   97.0397    3.7679    2.5323    0.2657   91.8240    4.5038   57.0000 
+2482.5250    8.5000    9.3898   98.4072    3.6836    2.5283    0.2600   92.6418    4.2330   57.0000 
+2482.6250    8.5000    9.4061   99.6710    3.7268    2.5302    0.2469   92.7158    3.8324   57.0000 
+2482.7250    8.5000    9.4225   99.4559    3.9143    2.5404    0.2363   92.1230    3.6842   57.0000 
+2482.8250    8.5000    9.4307   99.1909    4.2093    2.5524    0.2307   91.0270    3.7376   57.0000 
+2482.9250    8.5000    9.4388   99.6211    4.5061    2.5672    0.2309   89.7628    4.0417   57.0000 
+2483.0250    8.5000    9.4143  100.2242    4.6446    2.5783    0.2376   88.6704    4.4883   57.0000 
+2483.1250    8.5000    9.4061  103.0591    4.5115    2.5871    0.2489   87.9694    5.0386   57.0000 
+2483.2250    8.5000    9.3816  105.6866    4.1491    2.5886    0.2631   87.7510    5.5411   57.0000 
+2483.3250    8.5000    9.3816  105.8402    3.7065    2.5868    0.2715   87.9005    5.7859   57.0000 
+2483.4250    8.5000    9.3898  105.6097    3.3102    2.5797    0.2741   88.4005    5.7313   57.0000 
+2483.5250    8.5000    9.4061  104.5649    3.0150    2.5721    0.2723   88.9975    5.5188   57.0000 
+2483.6250    8.5000    9.4143  103.6122    2.8283    2.5660    0.2705   89.7898    5.3374   57.0000 
+2483.7250    8.5000    9.4307  104.6609    2.7361    2.5613    0.2687   90.3954    5.1812   57.0000 
+2483.8250    8.5000    9.4225  104.9260    2.7249    2.5617    0.2654   89.9872    5.0797   57.0000 
+2483.9250    8.5000    9.4061  103.1590    2.7918    2.5646    0.2634   88.3265    5.0728   57.0000 
+2484.0250    8.5000    9.3734  101.2690    2.9410    2.5700    0.2631   85.3418    5.1693   57.0000 
+2484.1250    8.5000    9.3816   99.3099    3.1717    2.5731    0.2663   83.0918    5.3410   57.0000 
+2484.2250    8.5000    9.3816   98.1422    3.4724    2.5667    0.2702   82.9490    5.3421   57.0000 
+2484.3250    8.5000    9.3898   99.2024    3.8251    2.5552    0.2752   84.9158    5.2783   57.0000 
+2484.4250    8.5000    9.3898   99.5174    4.2032    2.5424    0.2799   87.7480    5.1760   57.0000 
+2484.5250    8.5000    9.3734   99.3714    4.5492    2.5344    0.2806   89.7036    5.0395   57.0000 
+2484.6250    8.5000    9.3652   99.2178    4.7781    2.5303    0.2744   89.9077    4.7531   57.0000 
+2484.7250    8.5000    9.3570   97.5506    4.8637    2.5241    0.2585   88.9633    4.0997   57.0000 
+2484.8250    8.5000    9.3734   96.3060    4.8971    2.5227    0.2366   87.3541    3.3385   57.0000 
+2484.9250    8.5000    9.3652   94.2048    5.0277    2.5246    0.2115   85.1505    2.5405   57.0000 
+2485.0250    8.5000    9.3570   88.9422    5.3837    2.5371    0.1861   82.3821    1.9446   57.0000 
+2485.1250    8.5000    9.3816   82.0931    6.0580    2.5512    0.1616   78.6689    1.4093   57.0000 
+2485.2250    8.5000    9.3898   73.9418    7.1153    2.5650    0.1381   73.7561    0.9021   57.0000 
+2485.3250    8.5000    9.4307   64.9108    8.6299    2.5705    0.1187   69.1459    0.3650   57.0000 
+2485.4250    8.5000    9.4470   58.3345   10.7392    2.5725    0.1045   65.5643   -0.0664   54.0000 
+2485.5250    8.5000    9.4225   53.7018   13.6917    2.5713    0.0974   63.5908   -0.3279   25.0000 
+2485.6250    8.5000    9.4061   51.1973   17.5084    2.5682    0.0943   63.5051   -0.4915   25.0000 
+2485.7250    8.5000    9.3979   50.6019   21.1756    2.5596    0.0947   64.3760   -0.6510   25.0000 
+2485.8250    8.5000    9.4143   52.3842   21.7203    2.5499    0.0975   66.2225   -0.7517   25.0000 
+2485.9250    8.5000    9.4061   56.9285   20.0396    2.5468    0.1054   68.2607   -0.5493   25.0000 
+2486.0250    8.5000    9.4143   62.7366   17.8535    2.5459    0.1172   70.4342   -0.1737   54.0000 
+2486.1250    8.5000    9.3816   68.6139   15.9134    2.5447    0.1298   72.4934    0.2204   54.0000 
+2486.2250    8.5000    9.3979   71.9635   14.5817    2.5338    0.1378   74.2709    0.2678   54.0000 
+2486.3250    8.5000    9.3979   72.5551   13.7520    2.5298    0.1388   75.6699    0.2232   54.0000 
+2486.4250    8.5000    9.4061   70.3425   13.1802    2.5322    0.1353   76.1893    0.1537   54.0000 
+2486.5250    8.5000    9.3979   68.6753   12.7730    2.5476    0.1302   75.7337    0.2937   54.0000 
+2486.6250    8.5000    9.3898   68.8751   12.5180    2.5548    0.1277   74.6031    0.3526   57.0000 
+2486.7250    8.5000    9.3979   69.3284   12.3620    2.5528    0.1270   73.4276    0.2875   54.0000 
+2486.8250    8.5000    9.4307   71.5717   12.2527    2.5428    0.1276   72.9684    0.1108   54.0000 
+2486.9250    8.5000    9.4470   72.5167   12.1726    2.5390    0.1270   73.2561    0.0126   54.0000 
+2487.0250    8.5000    9.4552   71.6101   12.1253    2.5397    0.1265   74.0025    0.0086   54.0000 
+2487.1250    8.5000    9.4388   71.6216   12.0339    2.5434    0.1263   74.8658    0.0804   54.0000 
+2487.2250    8.5000    9.4061   71.2068   11.7870    2.5522    0.1298   75.3347    0.3699   57.0000 
+2487.3250    8.5000    9.4143   72.3092   11.3703    2.5699    0.1351   76.0087    0.9016   57.0000 
+2487.4250    8.5000    9.4061   74.4604   10.9259    2.5890    0.1420   76.5362    1.5140   57.0000 
+2487.5250    8.5000    9.4143   74.8560   10.5781    2.5927    0.1438   76.8944    1.6482   57.0000 
+2487.6250    8.5000    9.4225   74.6563   10.3349    2.5850    0.1389   76.9816    1.3282   57.0000 
+2487.7250    8.5000    9.4470   72.6588   10.1247    2.5705    0.1263   76.6898    0.6189   57.0000 
+2487.8250    8.5000    9.4716   68.6523    9.9037    2.5645    0.1128   76.2883    0.0494   54.0000 
+2487.9250    8.5000    9.4879   64.9223    9.7689    2.5626    0.1021   75.5148   -0.3455   25.0000 
+2488.0250    8.5000    9.4879   61.2308    9.8761    2.5712    0.0961   74.4995   -0.3729   25.0000 
+2488.1250    8.5000    9.4797   59.5675   10.2873    2.5845    0.0940   73.3628   -0.1768   54.0000 
+2488.2250    8.5000    9.4552   61.7264   10.8833    2.5988    0.0968   72.4107    0.2022   54.0000 
+2488.3250    8.5000    9.4716   67.2617   11.3832    2.6064    0.1050   71.8725    0.6282   57.0000 
+2488.4250    8.5000    9.4716   75.2210   11.4872    2.6072    0.1173   71.5010    1.0538   57.0000 
+2488.5250    8.5000    9.4716   82.3581   11.0439    2.6087    0.1292   71.4347    1.4789   57.0000 
+2488.6250    8.5000    9.4716   86.4530   10.2426    2.6092    0.1367   71.6143    1.7411   57.0000 
+2488.7250    8.5000    9.4552   86.0612    9.4310    2.6129    0.1389   72.1490    1.8898   57.0000 
+2488.8250    8.5000    9.4716   83.2762    8.8718    2.6140    0.1383   72.8908    1.8902   57.0000 
+2488.9250    8.5000    9.4634   82.0316    8.7052    2.6128    0.1393   73.3296    1.8984   57.0000 
+2489.0250    8.5000    9.4716   83.8524    8.9379    2.6052    0.1458   73.3505    1.9639   57.0000 
+2489.1250    8.5000    9.4716   88.8154    9.6140    2.5945    0.1574   73.1352    2.1381   57.0000 
+2489.2250    8.5000    9.4716   93.4289   10.6604    2.5937    0.1706   72.8775    2.5625   57.0000 
+2489.3250    8.5000    9.4879   93.9436   11.8015    2.6034    0.1811   72.3092    3.1053   57.0000 
+2489.4250    8.5000    9.4797   91.4045   12.6394    2.6162    0.1864   71.4765    3.5352   57.0000 
+2489.5250    8.5000    9.4634   88.0318   12.8209    2.6162    0.1883   70.4061    3.6019   57.0000 
+2489.6250    8.5000    9.4470   85.4581   12.3555    2.6104    0.1884   69.8796    3.4886   57.0000 
+2489.7250    8.5000    9.4470   86.6451   11.2161    2.6084    0.1878   70.2291    3.4294   57.0000 
+2489.8250    8.5000    9.4552   88.8116    9.5441    2.6176    0.1863   71.0342    3.5619   57.0000 
+2489.9250    8.5000    9.4879   90.5671    7.8134    2.6291    0.1844   72.3571    3.7274   57.0000 
+2490.0250    8.5000    9.4797   93.4173    6.4727    2.6364    0.1828   73.8566    3.8205   57.0000 
+2490.1250    8.5000    9.4716   95.5531    5.6448    2.6371    0.1818   75.7806    3.8010   57.0000 
+2490.2250    8.5000    9.4634   98.0346    5.2571    2.6335    0.1808   77.8827    3.6955   57.0000 
+2490.3250    8.5000    9.4552  100.5929    5.1752    2.6260    0.1829   79.2071    3.6169   57.0000 
+2490.4250    8.5000    9.4716  101.1000    5.2549    2.6168    0.1855   79.7561    3.5171   57.0000 
+2490.5250    8.5000    9.4879  101.1499    5.3674    2.6110    0.1895   79.3357    3.5373   57.0000 
+2490.6250    8.5000    9.4797  100.2741    5.4398    2.6151    0.1900   78.7571    3.6357   57.0000 
+2490.7250    8.5000    9.4552   98.5302    5.4742    2.6240    0.1903   78.3321    3.8217   57.0000 
+2490.8250    8.5000    9.4634   96.8054    5.5157    2.6234    0.1875   78.1163    3.7198   57.0000 
+2490.9250    8.5000    9.4470   93.3328    5.6260    2.6145    0.1849   78.2102    3.4525   57.0000 
+2491.0250    8.5000    9.4552   90.3212    5.8751    2.6062    0.1818   78.2806    3.1854   57.0000 
+2491.1250    8.5000    9.4388   87.8858    6.3420    2.6118    0.1808   78.3316    3.2617   57.0000 
+2491.2250    8.5000    9.4061   86.4300    7.0819    2.6237    0.1829   78.3541    3.5705   57.0000 
+2491.3250    8.5000    9.3570   86.9985    8.0679    2.6329    0.1887   78.3327    3.9473   57.0000 
+2491.4250    8.5000    9.3080   88.4428    9.1160    2.6363    0.1994   78.2551    4.3727   57.0000 
+2491.5250    8.5000    9.2507   90.8897    9.8364    2.6324    0.2106   78.3480    4.6684   57.0000 
+2491.6250    8.5000    9.2098   93.7016    9.8075    2.6274    0.2197   78.6061    4.8711   57.0000 
+2491.7250    8.5000    9.1444   95.2458    8.9789    2.6208    0.2235   79.3816    4.8671   57.0000 
+2491.8250    8.5000    9.1035   95.2074    7.7868    2.6212    0.2250   80.4469    4.9247   57.0000 
+2491.9250    8.5000    9.0544   93.8706    6.7095    2.6239    0.2259   81.6041    5.0072   57.0000 
+2492.0250    8.5000    9.0053   92.3840    5.9685    2.6278    0.2277   82.7082    5.1456   57.0000 
+2492.1250    8.5000    8.9971   92.8604    5.5866    2.6237    0.2289   83.5005    5.1021   57.0000 
+2492.2250    8.5000    8.9726   94.5237    5.5059    2.6144    0.2318   84.0398    5.0153   57.0000 
+2492.3250    8.5000    8.9235   97.0704    5.6497    2.6006    0.2353   84.4153    4.8542   57.0000 
+2492.4250    8.5000    8.9481   99.2139    5.9179    2.5911    0.2419   84.7000    4.8847   57.0000 
+2492.5250    8.5000    8.9153   99.9054    6.1836    2.5856    0.2444   85.1000    4.8577   57.0000 
+2492.6250    8.5000    8.8990  100.5661    6.3067    2.5913    0.2456   85.4439    5.0114   57.0000 
+2492.7250    8.5000    8.8908  101.8798    6.2109    2.5964    0.2434   85.5469    5.0422   57.0000 
+2492.8250    8.5000    8.8663  104.3767    5.9338    2.6052    0.2461   85.2791    5.3068   57.0000 
+2492.9250    8.5000    8.8417  106.5739    5.5885    2.6043    0.2504   84.7893    5.4339   57.0000 
+2493.0250    8.5000    8.8581  108.3601    5.2818    2.6048    0.2565   84.5383    5.6468   57.0000 
+2493.1250    8.5000    8.8744  107.9798    5.0676    2.6002    0.2601   84.8209    5.6717   57.0000 
+2493.2250    8.5000    8.8990  105.3063    4.9493    2.5975    0.2597   85.5730    5.6072   57.0000 
+2493.3250    8.5000    8.8908  103.4855    4.8969    2.5949    0.2566   86.2413    5.4534   57.0000 
+2493.4250    8.5000    8.9153  101.3497    4.8735    2.5949    0.2539   86.5745    5.3634   57.0000 
+2493.5250    8.5000    8.8908   99.7056    4.8469    2.5952    0.2555   86.4796    5.4208   57.0000 
+2493.6250    8.5000    8.8908   99.6288    4.8020    2.5939    0.2583   86.2454    5.4889   57.0000 
+2493.7250    8.5000    8.8990   98.8989    4.7395    2.5936    0.2589   86.0852    5.5024   57.0000 
+2493.8250    8.5000    8.8663   98.1307    4.6656    2.5947    0.2557   85.9587    5.4176   57.0000 
+2493.9250    8.5000    8.8826   97.6006    4.5806    2.6006    0.2503   86.1673    5.3556   57.0000 
+2494.0250    8.5000    8.8499   96.8169    4.4913    2.6006    0.2438   86.9276    5.1381   57.0000 
+2494.1250    8.5000    8.8744   96.5634    4.4258    2.6010    0.2373   87.4240    4.9297   57.0000 
+2494.2250    8.5000    8.8826   96.3022    4.4318    2.5941    0.2327   87.4628    4.6376   57.0000 
+2494.3250    8.5000    8.8744   96.3790    4.5487    2.5914    0.2308   85.7878    4.5226   57.0000 
+2494.4250    8.5000    8.8581   95.3188    4.7779    2.5874    0.2309   83.4883    4.4449   57.0000 
+2494.5250    8.5000    8.8254   95.1344    5.0842    2.5888    0.2341   81.5612    4.5783   57.0000 
+2494.6250    8.5000    8.8172   95.9949    5.4217    2.5909    0.2383   80.4679    4.7607   57.0000 
+2494.7250    8.5000    8.8090   97.4546    5.7699    2.5949    0.2432   80.5765    5.0048   57.0000 
+2494.8250    8.5000    8.8172   99.8132    6.1442    2.5948    0.2451   81.1357    5.0649   57.0000 
+2494.9250    8.5000    8.8254   98.9719    6.5569    2.5935    0.2447   82.0367    5.0276   57.0000 
+2495.0250    8.5000    8.8172   95.9449    6.9542    2.5905    0.2444   82.9995    4.9565   57.0000 
+2495.1250    8.5000    8.7845   92.7413    7.2422    2.5917    0.2440   83.8398    4.9683   57.0000 
+2495.2250    8.5000    8.8254   89.2687    7.3644    2.5914    0.2457   84.0617    5.0186   57.0000 
+2495.3250    8.5000    8.8172   88.8999    7.3389    2.5871    0.2444   83.6510    4.8887   57.0000 
+2495.4250    8.5000    8.8499   90.9973    7.2098    2.5782    0.2421   82.9332    4.6354   57.0000 
+2495.5250    8.5000    8.8417   92.9525    7.0370    2.5730    0.2364   82.3077    4.3395   57.0000 
+2495.6250    8.5000    8.8090   95.8873    6.8844    2.5735    0.2320   82.3352    4.2039   57.0000 
+2495.7250    8.5000    8.8254   98.3458    6.7987    2.5797    0.2284   82.8321    4.2088   57.0000 
+2495.8250    8.5000    8.8663  100.3855    6.7813    2.5862    0.2268   83.5270    4.2849   57.0000 
+2495.9250    8.5000    8.8663  101.2844    6.7728    2.5893    0.2286   83.9546    4.4056   57.0000 
+2496.0250    8.5000    8.8744  102.3100    6.6723    2.5906    0.2340   84.1480    4.6128   57.0000 
+2496.1250    8.5000    8.8826  102.6711    6.4060    2.5872    0.2407   84.2250    4.7680   57.0000 
+2496.2250    8.5000    8.8254  102.1487    6.0111    2.5880    0.2445   84.2862    4.9103   57.0000 
+2496.3250    8.5000    8.8335  101.8760    5.6175    2.5834    0.2450   84.2418    4.8341   57.0000 
+2496.4250    8.5000    8.8172   99.2600    5.3375    2.5805    0.2442   83.9821    4.7525   57.0000 
+2496.5250    8.5000    8.7845   96.0947    5.2063    2.5750    0.2438   83.5107    4.6270   57.0000 
+2496.6250    8.5000    8.7926   93.5940    5.1947    2.5765    0.2430   82.9240    4.6299   57.0000 
+2496.7250    8.5000    8.7681   93.3828    5.2549    2.5777    0.2447   82.3066    4.7112   57.0000 
+2496.8250    8.5000    8.7845   95.3303    5.3525    2.5761    0.2468   81.7265    4.7482   57.0000 
+2496.9250    8.5000    8.8008   98.7414    5.4729    2.5700    0.2484   81.3643    4.6785   57.0000 
+2497.0250    8.5000    8.8254  101.4112    5.5966    2.5677    0.2468   81.3765    4.5818   57.0000 
+2497.1250    8.5000    8.8254  101.7684    5.6786    2.5729    0.2453   81.5617    4.6341   57.0000 
+2497.2250    8.5000    8.8172  101.5648    5.6777    2.5790    0.2456   81.6311    4.7669   57.0000 
+2497.3250    8.5000    8.8254   99.0257    5.5987    2.5818    0.2456   81.4648    4.8221   57.0000 
+2497.4250    8.5000    8.8254   96.6594    5.4965    2.5818    0.2423   81.2199    4.7115   57.0000 
+2497.5250    8.5000    8.8744   95.0883    5.4277    2.5823    0.2367   81.1934    4.5355   57.0000 
+2497.6250    8.5000    8.8990   93.2752    5.4185    2.5813    0.2312   81.3505    4.3335   57.0000 
+2497.7250    8.5000    8.8826   93.2791    5.4599    2.5751    0.2292   81.5327    4.1412   57.0000 
+2497.8250    8.5000    8.8417   94.0473    5.5333    2.5704    0.2280   81.5842    4.0087   57.0000 
+2497.9250    8.5000    8.8417   94.7349    5.6318    2.5733    0.2291   81.6173    4.1045   57.0000 
+2498.0250    8.5000    8.8254   95.3073    5.7569    2.5830    0.2313   81.6918    4.3718   57.0000 
+2498.1250    8.5000    8.8254   95.7183    5.8982    2.5913    0.2368   81.8010    4.7185   57.0000 
+2498.2250    8.5000    8.8172   95.1728    6.0231    2.5895    0.2414   81.8929    4.8345   57.0000 
+2498.3250    8.5000    8.8172   93.1484    6.0873    2.5835    0.2450   81.9301    4.8365   57.0000 
+2498.4250    8.5000    8.8335   91.6772    6.0605    2.5784    0.2452   81.9964    4.7431   57.0000 
+2498.5250    8.5000    8.8499   89.8948    5.9549    2.5812    0.2435   82.0429    4.7406   57.0000 
+2498.6250    8.5000    8.8417   88.3698    5.8156    2.5845    0.2390   82.0490    4.6582   57.0000 
+2498.7250    8.5000    8.8172   89.9371    5.6859    2.5861    0.2361   82.0194    4.5918   57.0000 
+2498.8250    8.5000    8.8008   91.5044    5.5870    2.5814    0.2348   82.0046    4.4567   57.0000 
+2498.9250    8.5000    8.8008   95.0077    5.5180    2.5787    0.2368   82.0872    4.4675   57.0000 
+2499.0250    8.5000    8.7926   99.2408    5.4629    2.5816    0.2364   82.1561    4.5122   57.0000 
+2499.1250    8.5000    8.8172  101.5879    5.3971    2.5851    0.2379   82.1735    4.6318   57.0000 
+2499.2250    8.5000    8.8499  104.1884    5.3083    2.5835    0.2404   81.9383    4.6821   57.0000 
+2499.3250    8.5000    8.8417  104.4881    5.2093    2.5695    0.2461   81.5281    4.5919   57.0000 
+2499.4250    8.5000    8.8499  104.0041    5.1299    2.5652    0.2503   81.0883    4.6479   57.0000 
+2499.5250    8.5000    8.8335  103.4663    5.0886    2.5655    0.2491   80.8673    4.6153   57.0000 
+2499.6250    8.5000    8.8335  101.5917    5.0770    2.5765    0.2456   81.2561    4.7166   57.0000 
+2499.7250    8.5000    8.8254   99.1371    5.0705    2.5768    0.2421   82.0903    4.6043   57.0000 
+2499.8250    8.5000    8.8090   96.5096    5.0532    2.5775    0.2444   83.0862    4.6961   57.0000 
+2499.9250    8.5000    8.8008   94.5390    5.0293    2.5752    0.2490   83.6469    4.8030   57.0000 
+2500.0250    8.5000    8.8008   94.4622    5.0110    2.5753    0.2528   83.6046    4.9314   57.0000 
+2500.1250    8.5000    8.7926   96.1216    4.9934    2.5734    0.2538   83.2821    4.9283   57.0000 
+2500.2250    8.5000    8.8335   98.5647    4.9498    2.5715    0.2535   83.1735    4.8805   57.0000 
+2500.3250    8.5000    8.8254  100.3817    4.8596    2.5741    0.2531   83.3908    4.9203   57.0000 
+2500.4250    8.5000    8.8172   99.8861    4.7329    2.5804    0.2520   83.6434    5.0087   57.0000 
+2500.5250    8.5000    8.7845   99.2638    4.6096    2.5875    0.2511   83.7015    5.1193   57.0000 
+2500.6250    8.5000    8.7845   97.5468    4.5368    2.5890    0.2529   83.3964    5.2102   57.0000 
+2500.7250    8.5000    8.8008   95.8028    4.5456    2.5843    0.2559   83.0383    5.2163   57.0000 
+2500.8250    8.5000    8.8335   95.4648    4.6450    2.5777    0.2553   82.7403    5.0628   57.0000 
+2500.9250    8.5000    8.8335   94.5621    4.8116    2.5738    0.2477   82.4985    4.7311   57.0000 
+2501.0250    8.5000    8.8335   95.5992    4.9723    2.5737    0.2387   82.1730    4.4294   57.0000 
+2501.1250    8.5000    8.8254   97.2433    5.0248    2.5805    0.2326   81.6056    4.3634   57.0000 
+2501.2250    8.5000    8.8499   99.7824    4.9308    2.5882    0.2312   80.9643    4.4690   57.0000 
+2501.3250    8.5000    8.8254  101.8106    4.7645    2.5973    0.2300   80.3990    4.6117   57.0000 
+2501.4250    8.5000    8.8417  101.3113    4.6395    2.5969    0.2270   80.0352    4.5027   57.0000 
+2501.5250    8.5000    8.8499   99.7824    4.6245    2.5921    0.2237   79.7740    4.2992   57.0000 
+2501.6250    8.5000    8.8744   96.0832    4.7203    2.5829    0.2198   79.4888    3.9846   57.0000 
+2501.7250    8.5000    8.9235   92.6721    4.8785    2.5731    0.2185   79.0898    3.7455   57.0000 
+2501.8250    8.5000    8.9726   90.8667    5.0340    2.5654    0.2155   78.6571    3.4898   57.0000 
+2501.9250    8.5000    9.0217   90.1445    5.1498    2.5585    0.2138   78.2199    3.2989   57.0000 
+2502.0250    8.5000    9.0462   91.5351    5.2225    2.5640    0.2115   77.7714    3.3287   57.0000 
+2502.1250    8.5000    9.0789   93.4442    5.2669    2.5733    0.2109   77.4342    3.4984   57.0000 
+2502.2250    8.5000    9.0789   95.6914    5.2996    2.5862    0.2113   77.3587    3.7656   57.0000 
+2502.3250    8.5000    9.0626   97.7196    5.3235    2.5923    0.2118   77.7811    3.9079   57.0000 
+2502.4250    8.5000    9.0626   97.2318    5.3141    2.5979    0.2140   78.6474    4.0929   57.0000 
+2502.5250    8.5000    9.0708   96.0640    5.2334    2.6045    0.2151   79.8209    4.2589   57.0000 
+2502.6250    8.5000    9.1035   93.6017    5.0763    2.6090    0.2177   81.0923    4.4377   57.0000 
+2502.7250    8.5000    9.1280   89.7028    4.8901    2.6124    0.2200   82.2306    4.5795   57.0000 
+2502.8250    8.5000    9.1771   88.4928    4.7411    2.6144    0.2250   83.2092    4.7899   57.0000 
+2502.9250    8.5000    9.1689   88.6349    4.6608    2.6162    0.2296   83.8827    4.9796   57.0000 
+2503.0250    8.5000    9.1689   89.7719    4.6370    2.6133    0.2342   84.2592    5.0727   57.0000 
+2503.1250    8.5000    9.1607   93.4481    4.6329    2.6057    0.2379   84.6429    5.0459   57.0000 
+2503.2250    8.5000    9.1444   95.3380    4.6092    2.5977    0.2430   85.1337    5.0546   57.0000 
+2503.3250    8.5000    9.1362   96.2254    4.5342    2.5878    0.2483   86.0214    5.0351   57.0000 
+2503.4250    8.5000    9.1280   96.5595    4.4030    2.5780    0.2515   87.0286    4.9414   57.0000 
+2503.5250    8.5000    9.1362   96.1101    4.2503    2.5695    0.2498   87.9025    4.7186   57.0000 
+2503.6250    8.5000    9.1525   96.6748    4.1459    2.5736    0.2444   88.2760    4.6183   57.0000 
+2503.7250    8.5000    9.1525   97.2740    4.1647    2.5807    0.2383   88.1929    4.5568   57.0000 
+2503.8250    8.5000    9.1689   97.8656    4.3460    2.5851    0.2344   87.7582    4.5164   57.0000 
+2503.9250    8.5000    9.1689   96.6825    4.6558    2.5789    0.2329   87.1658    4.3411   57.0000 
+2504.0250    8.5000    9.1771   94.8770    4.9670    2.5717    0.2329   86.5872    4.1972   57.0000 
+2504.1250    8.5000    9.1853   92.7528    5.1110    2.5770    0.2336   85.9485    4.3273   57.0000 
+2504.2250    8.5000    9.1689   91.1625    5.0229    2.5923    0.2339   85.3949    4.6420   57.0000 
+2504.3250    8.5000    9.1853   91.8923    4.7913    2.6196    0.2329   84.9582    5.1555   57.0000 
+2504.4250    8.5000    9.1853   93.6747    4.5621    2.6370    0.2313   84.7592    5.4507   57.0000 
+2504.5250    8.5000    9.2016   96.8784    4.4741    2.6455    0.2326   84.9689    5.6644   57.0000 
+2504.6250    8.5000    9.2098  100.0129    4.5576    2.6343    0.2384   85.4704    5.6313   57.0000 
+2504.7250    8.5000    9.2016  101.5610    4.8618    2.6165    0.2427   86.2622    5.4184   57.0000 
+2504.8250    8.5000    9.2098  102.1756    5.3493    2.6013    0.2444   87.1821    5.1726   57.0000 
+2504.9250    8.5000    9.2016  101.7991    5.8630    2.5915    0.2398   88.0699    4.8243   57.0000 
+2505.0250    8.5000    9.2098  101.1692    6.1252    2.5851    0.2379   88.8122    4.6317   57.0000 
+2505.1250    8.5000    9.2180  101.4380    6.1081    2.5741    0.2354   89.2566    4.3298   57.0000 
+2505.2250    8.5000    9.2180  101.2882    5.9493    2.5690    0.2360   89.3505    4.2465   57.0000 
+2505.3250    8.5000    9.1934   99.7747    5.7750    2.5701    0.2356   89.2235    4.2558   57.0000 
+2505.4250    8.5000    9.2262   97.6236    5.6197    2.5761    0.2343   88.9857    4.3303   57.0000 
+2505.5250    8.5000    9.1934   94.1664    5.4800    2.5845    0.2340   88.7811    4.4903   57.0000 
+2505.6250    8.5000    9.2016   91.6542    5.3573    2.5938    0.2352   88.6893    4.7149   57.0000 
+2505.7250    8.5000    9.2180   90.6170    5.2524    2.6021    0.2402   88.7306    5.0482   57.0000 
+2505.8250    8.5000    9.1934   89.7834    5.1482    2.6031    0.2444   88.8362    5.2104   57.0000 
+2505.9250    8.5000    9.1771   90.9474    5.0421    2.5981    0.2476   89.0260    5.2152   57.0000 
+2506.0250    8.5000    9.1853   90.6631    4.9549    2.5932    0.2484   89.2020    5.1430   57.0000 
+2506.1250    8.5000    9.1771   91.5236    4.9286    2.5845    0.2478   89.2270    4.9495   57.0000 
+2506.2250    8.5000    9.2098   94.0435    4.9789    2.5744    0.2461   89.0760    4.6913   57.0000 
+2506.3250    8.5000    9.2180   94.7080    5.0747    2.5659    0.2432   88.7750    4.4254   57.0000 
+2506.4250    8.5000    9.2507   95.9834    5.1342    2.5686    0.2412   88.3628    4.4132   57.0000 
+2506.5250    8.5000    9.2507   96.1140    5.0911    2.5821    0.2387   87.9143    4.5977   57.0000 
+2506.6250    8.5000    9.2262   95.0230    4.9592    2.5998    0.2368   87.4423    4.8877   57.0000 
+2506.7250    8.5000    9.2262   94.2010    4.7996    2.6143    0.2343   87.0122    5.0963   57.0000 
+2506.8250    8.5000    9.2016   94.8924    4.6529    2.6209    0.2353   86.6556    5.2613   57.0000 
+2506.9250    8.5000    9.2016   94.6619    4.5306    2.6185    0.2387   86.5020    5.3256   57.0000 
+2507.0250    8.5000    9.1934   94.0550    4.4489    2.6119    0.2436   86.8061    5.3572   57.0000 
+2507.1250    8.5000    9.2098   94.5621    4.4570    2.6005    0.2453   87.4612    5.1857   57.0000 
+2507.2250    8.5000    9.2343   92.8143    4.6390    2.5928    0.2447   88.3500    5.0103   57.0000 
+2507.3250    8.5000    9.2425   91.9154    5.0922    2.5889    0.2421   88.8837    4.8473   57.0000 
+2507.4250    8.5000    9.2507   90.0139    5.8959    2.5945    0.2396   88.9964    4.8743   57.0000 
+2507.5250    8.5000    9.2589   87.2021    6.9682    2.6039    0.2362   88.7000    4.9536   57.0000 
+2507.6250    8.5000    9.2998   85.4427    7.8548    2.6070    0.2337   88.1684    4.9288   57.0000 
+2507.7250    8.5000    9.3407   83.2224    7.9738    2.6039    0.2330   87.5832    4.8432   57.0000 
+2507.8250    8.5000    9.3161   84.0368    7.4107    2.5903    0.2342   87.1107    4.6137   57.0000 
+2507.9250    8.5000    9.3489   86.8679    6.7012    2.5792    0.2371   86.8214    4.4866   57.0000 
+2508.0250    8.5000    9.3080   91.0665    6.1290    2.5706    0.2376   86.6735    4.3317   57.0000 
+2508.1250    8.5000    9.3161   95.9872    5.7037    2.5668    0.2381   86.5592    4.2711   57.0000 
+2508.2250    8.5000    9.3161   99.3599    5.3559    2.5657    0.2377   86.3995    4.2379   57.0000 
+2508.3250    8.5000    9.3161  100.0628    5.0394    2.5617    0.2390   86.2781    4.2002   57.0000 
+2508.4250    8.5000    9.3243  100.4470    4.7397    2.5647    0.2392   86.2546    4.2670   57.0000 
+2508.5250    8.5000    9.2671  101.1423    4.4653    2.5711    0.2384   86.3189    4.3703   57.0000 
+2508.6250    8.5000    9.2998  101.8030    4.2311    2.5839    0.2393   86.5408    4.6549   57.0000 
+2508.7250    8.5000    9.3080  103.6430    4.0473    2.5904    0.2427   86.8852    4.8977   57.0000 
+2508.8250    8.5000    9.3161  104.0271    3.9181    2.5922    0.2469   87.3699    5.0742   57.0000 
+2508.9250    8.5000    9.3325  103.5930    3.8465    2.5867    0.2481   87.9464    5.0052   57.0000 
+2509.0250    8.5000    9.3161  102.5636    3.8355    2.5843    0.2454   88.4918    4.8669   57.0000 
+2509.1250    8.5000    9.3161  100.9118    3.8798    2.5810    0.2422   88.9046    4.6944   57.0000 
+2509.2250    8.5000    9.3407   99.8132    3.9601    2.5864    0.2397   88.9903    4.7202   57.0000 
+2509.3250    8.5000    9.3734   98.6876    4.0452    2.5924    0.2380   88.7301    4.7813   57.0000 
+2509.4250    8.5000    9.4061   97.7657    4.1083    2.6033    0.2356   88.3276    4.9192   57.0000 
+2509.5250    8.5000    9.4307   98.0807    4.1373    2.6044    0.2344   87.9316    4.9016   57.0000 
+2509.6250    8.5000    9.4307   98.1960    4.1351    2.6015    0.2344   87.7969    4.8413   57.0000 
+2509.7250    8.5000    9.4225   98.7337    4.1158    2.5930    0.2355   87.8388    4.7111   57.0000 
+2509.8250    8.5000    9.4307   99.5020    4.0948    2.5911    0.2359   87.9449    4.6864   57.0000 
+2509.9250    8.5000    9.4061   98.9681    4.0832    2.5867    0.2378   88.0714    4.6617   57.0000 
+2510.0250    8.5000    9.3979   98.6070    4.0849    2.5812    0.2404   88.1327    4.6375   57.0000 
+2510.1250    8.5000    9.4061   98.2036    4.0964    2.5755    0.2434   88.1367    4.6221   57.0000 
+2510.2250    8.5000    9.3979   98.4226    4.1093    2.5758    0.2442   88.0378    4.6577   57.0000 
+2510.3250    8.5000    9.4143   99.1448    4.1197    2.5828    0.2443   87.9648    4.7998   57.0000 
+2510.4250    8.5000    9.4225   99.5673    4.1342    2.5861    0.2458   88.0699    4.9173   57.0000 
+2510.5250    8.5000    9.4225   99.8208    4.1810    2.5894    0.2478   88.4107    5.0476   57.0000 
+2510.6250    8.5000    9.4061   99.7594    4.3022    2.5897    0.2476   88.9408    5.0462   57.0000 
+2510.7250    8.5000    9.4143   98.4841    4.5210    2.5928    0.2422   89.3684    4.9303   57.0000 
+2510.8250    8.5000    9.4225   98.0077    4.7993    2.5920    0.2354   89.5260    4.6861   57.0000 
+2510.9250    8.5000    9.4388   97.9578    4.9953    2.5907    0.2304   89.3546    4.4960   57.0000 
+2511.0250    8.5000    9.4552   97.6889    4.9377    2.5847    0.2294   88.9474    4.3400   57.0000 
+2511.1250    8.5000    9.4634   99.1102    4.6276    2.5805    0.2298   88.5173    4.2705   57.0000 
+2511.2250    8.5000    9.4552   99.2638    4.2371    2.5742    0.2305   88.1020    4.1671   57.0000 
+2511.3250    8.5000    9.4797   98.8643    3.9118    2.5725    0.2293   87.6888    4.0948   57.0000 
+2511.4250    8.5000    9.4961   98.5109    3.7007    2.5729    0.2287   87.2112    4.0810   57.0000 
+2511.5250    8.5000    9.4797   98.7107    3.5998    2.5736    0.2263   86.7204    4.0153   57.0000 
+2511.6250    8.5000    9.4797  100.1704    3.5839    2.5743    0.2247   86.4112    3.9778   57.0000 
+2511.7250    8.5000    9.4552  101.1692    3.6251    2.5747    0.2220   86.3847    3.8929   57.0000 
+2511.8250    8.5000    9.4716  100.8811    3.6977    2.5752    0.2215   86.6770    3.8887   57.0000 
+2511.9250    8.5000    9.4961   99.3829    3.7811    2.5733    0.2222   87.0847    3.8720   57.0000 
+2512.0250    8.5000    9.4879   96.5711    3.8592    2.5667    0.2248   87.5296    3.8273   57.0000 
+2512.1250    8.5000    9.4716   95.5685    3.9236    2.5665    0.2298   87.9893    3.9915   57.0000 
+2512.2250    8.5000    9.4879   96.4520    3.9695    2.5702    0.2356   88.4725    4.2573   57.0000 
+2512.3250    8.5000    9.4797   96.4597    3.9898    2.5811    0.2419   89.0429    4.6838   57.0000 
+2512.4250    8.5000    9.4797   96.9206    3.9746    2.5889    0.2438   89.4617    4.9042   57.0000 
+2512.5250    8.5000    9.5043   94.8847    3.9250    2.5962    0.2440   89.5980    5.0573   57.0000 
+2512.6250    8.5000    9.4388   92.5646    3.8649    2.5972    0.2418   89.4138    5.0044   57.0000 
+2512.7250    8.5000    9.4307   92.7182    3.8300    2.5936    0.2397   89.0051    4.8614   57.0000 
+2512.8250    8.5000    9.4388   94.2855    3.8424    2.5876    0.2373   88.5811    4.6615   57.0000 
+2512.9250    8.5000    9.4552   97.2471    3.8902    2.5816    0.2380   88.3505    4.5646   57.0000 
+2513.0250    8.5000    9.4634   98.9412    3.9368    2.5753    0.2428   89.5719    4.5974   57.0000 
+2513.1250    8.5000    9.4634   98.6262    3.9516    2.5672    0.2495   92.8913    4.6609   57.0000 
+2513.2250    8.5000    9.4470   96.8284    3.9351    2.5631    0.2512   98.1459    4.6356   57.0000 
+2513.3250    8.5000    9.4552   94.8156    3.9131    2.5659    0.2461  103.2015    4.5210   57.0000 
+2513.4250    8.5000    9.4470   93.7170    3.9181    2.5781    0.2384  104.3577    4.5094   57.0000 
+2513.5250    8.5000    9.4225   93.0178    3.9718    2.5888    0.2328  101.5291    4.5382   57.0000 
+2513.6250    8.5000    9.4225   92.9103    4.0758    2.5969    0.2312   95.5342    4.6435   57.0000 
+2513.7250    8.5000    9.4307   93.1715    4.2028    2.5963    0.2286   90.6679    4.5462   57.0000 
+2513.8250    8.5000    9.4552   93.9513    4.2881    2.5930    0.2275   87.9597    4.4453   57.0000 
+2513.9250    8.5000    9.4716   93.7823    4.2653    2.5836    0.2281   87.4138    4.2740   57.0000 
+2514.0250    8.5000    9.4470   92.9602    4.1329    2.5709    0.2317   87.8663    4.1418   57.0000 
+2514.1250    8.5000    9.4552   92.3687    3.9617    2.5639    0.2337   88.4959    4.0665   57.0000 
+2514.2250    8.5000    9.4388   91.3085    3.8225    2.5627    0.2329   89.1531    4.0189   57.0000 
+2514.3250    8.5000    9.4388   92.6913    3.7433    2.5702    0.2325   89.6133    4.1535   57.0000 
+2514.4250    8.5000    9.4552   95.2497    3.7121    2.5737    0.2346   89.8418    4.2933   57.0000 
+2514.5250    8.5000    9.4634   96.9629    3.7056    2.5783    0.2387   89.8694    4.5233   57.0000 
+2514.6250    8.5000    9.4388   97.8771    3.7055    2.5813    0.2414   89.6923    4.6723   57.0000 
+2514.7250    8.5000    9.4307   96.5941    3.7032    2.5862    0.2422   89.3750    4.7987   57.0000 
+2514.8250    8.5000    9.4388   94.5429    3.6937    2.5893    0.2422   89.0811    4.8584   57.0000 
+2514.9250    8.5000    9.4061   93.5825    3.6773    2.5868    0.2404   89.0388    4.7501   57.0000 
+2515.0250    8.5000    9.3898   94.3815    3.6594    2.5780    0.2374   89.5311    4.4722   57.0000 
+2515.1250    8.5000    9.3898   96.1101    3.6473    2.5653    0.2343   90.2301    4.1156   57.0000 
+2515.2250    8.5000    9.3898   96.7478    3.6443    2.5552    0.2336   90.9107    3.8916   57.0000 
+2515.3250    8.5000    9.3652   94.7272    3.6482    2.5492    0.2371   91.2444    3.8871   57.0000 
+2515.4250    8.5000    9.3734   90.6016    3.6558    2.5470    0.2404   91.1393    3.9516   57.0000 
+2515.5250    8.5000    9.3570   87.5747    3.6670    2.5492    0.2425   90.8158    4.0672   57.0000 
+2515.6250    8.5000    9.3570   86.5913    3.6853    2.5585    0.2409   90.3495    4.1990   57.0000 
+2515.7250    8.5000    9.3243   88.3890    3.7117    2.5730    0.2378   90.0184    4.3853   57.0000 
+2515.8250    8.5000    9.2998   91.5773    3.7428    2.5842    0.2355   89.8827    4.5325   57.0000 
+2515.9250    8.5000    9.2916   93.5595    3.7735    2.5828    0.2357   90.0158    4.5143   57.0000 
+2516.0250    8.5000    9.3161   95.3111    3.7989    2.5741    0.2391   90.3031    4.4522   57.0000 
+2516.1250    8.5000    9.3407   95.7106    3.8159    2.5654    0.2420   90.4913    4.3742   57.0000 
+2516.2250    8.5000    9.3489   95.1882    3.8240    2.5676    0.2429   90.5811    4.4471   57.0000 
+2516.3250    8.5000    9.3325   94.3969    3.8237    2.5721    0.2410   90.4964    4.4762   57.0000 
+2516.4250    8.5000    9.3243   93.8015    3.8127    2.5738    0.2393   90.3883    4.4540   57.0000 
+2516.5250    8.5000    9.2916   95.5839    3.7960    2.5699    0.2376   90.2658    4.3177   57.0000 
+2516.6250    8.5000    9.2752  100.5238    3.7950    2.5639    0.2369   90.1704    4.1743   57.0000 
+2516.7250    8.5000    9.2916  106.3089    3.8446    2.5632    0.2343   90.0913    4.0731   57.0000 
+2516.8250    8.5000    9.2916  109.7276    3.9783    2.5656    0.2311   90.0337    4.0154   57.0000 
+2516.9250    8.5000    9.3080  109.3973    4.1955    2.5756    0.2282   89.9679    4.1185   57.0000 
+2517.0250    8.5000    9.3161  104.2499    4.4438    2.5820    0.2271   89.7755    4.2117   57.0000 
+2517.1250    8.5000    9.2998   98.0269    4.6479    2.5858    0.2283   89.2724    4.3255   57.0000 
+2517.2250    8.5000    9.2916   94.3124    4.7699    2.5792    0.2295   88.3929    4.2328   57.0000 
+2517.3250    8.5000    9.2671   92.7912    4.8211    2.5705    0.2313   87.2423    4.1187   57.0000 
+2517.4250    8.5000    9.2343   94.5044    4.8261    2.5598    0.2303   86.1959    3.8720   57.0000 
+2517.5250    8.5000    9.2180   97.1626    4.7949    2.5557    0.2288   85.4388    3.7391   57.0000 
+2517.6250    8.5000    9.2343   98.1153    4.7405    2.5553    0.2275   85.0954    3.6904   57.0000 
+2517.7250    8.5000    9.2262   98.5686    4.6902    2.5564    0.2312   85.1444    3.8353   57.0000 
+2517.8250    8.5000    9.2262   97.6467    4.6743    2.5599    0.2357   85.5071    4.0539   57.0000 
+2517.9250    8.5000    9.2016   96.1255    4.7021    2.5667    0.2418   86.1357    4.3927   57.0000 
+2518.0250    8.5000    9.1934   93.9129    4.7621    2.5774    0.2449   86.8306    4.7112   57.0000 
+2518.1250    8.5000    9.1934   92.2534    4.8245    2.5857    0.2465   87.3872    4.9318   57.0000 
+2518.2250    8.5000    9.1853   90.8014    4.8500    2.5937    0.2442   87.6949    5.0131   57.0000 
+2518.3250    8.5000    9.1771   88.8577    4.8087    2.5986    0.2418   87.7173    5.0320   57.0000 
+2518.4250    8.5000    9.1689   89.2111    4.7087    2.5994    0.2420   87.6352    5.0570   57.0000 
+2518.5250    8.5000    9.1525   88.1662    4.5917    2.5951    0.2451   87.5173    5.0737   57.0000 
+2518.6250    8.5000    9.1362   87.6746    4.4977    2.5899    0.2499   87.5122    5.1264   57.0000 
+2518.7250    8.5000    9.1035   88.0587    4.4428    2.5831    0.2532   87.8612    5.1022   57.0000 
+2518.8250    8.5000    9.0462   87.2443    4.4317    2.5738    0.2547   88.5352    4.9677   57.0000 
+2518.9250    8.5000    9.0053   88.5657    4.4763    2.5602    0.2524   89.5663    4.6192   57.0000 
+2519.0250    8.5000    9.0217   89.8487    4.5947    2.5537    0.2463   90.6133    4.2814   57.0000 
+2519.1250    8.5000    9.0217   91.0165    4.7868    2.5521    0.2380   91.3980    3.9756   57.0000 
+2519.2250    8.5000    9.0299   92.5223    4.9966    2.5602    0.2319   91.7577    3.9356   57.0000 
+2519.3250    8.5000    9.0299   92.5607    5.1255    2.5672    0.2298   91.6036    4.0047   57.0000 
+2519.4250    8.5000    9.0380   91.4928    5.1183    2.5750    0.2317   91.0184    4.2218   57.0000 
+2519.5250    8.5000    9.0380   90.1100    5.0034    2.5804    0.2338   90.3214    4.4002   57.0000 
+2519.6250    8.5000    9.0135   89.0958    4.8387    2.5796    0.2379   89.7347    4.5227   57.0000 
+2519.7250    8.5000    9.0217   88.4966    4.6592    2.5768    0.2411   89.4362    4.5743   57.0000 
+2519.8250    8.5000    8.9890   89.2572    4.4863    2.5692    0.2436   89.2714    4.5025   57.0000 
+2519.9250    8.5000    8.9890   90.4557    4.3520    2.5656    0.2410   89.0719    4.3458   57.0000 
+2520.0250    8.5000    8.9971   91.9077    4.2987    2.5634    0.2370   88.7791    4.1670   57.0000 
+2520.1250    8.5000    8.9726   92.9449    4.3506    2.5660    0.2340   88.5066    4.1216   57.0000 
+2520.2250    8.5000    8.9562   93.0831    4.4943    2.5717    0.2348   88.3367    4.2597   57.0000 
+2520.3250    8.5000    8.9481   93.5595    4.6778    2.5734    0.2366   88.2638    4.3531   57.0000 
+2520.4250    8.5000    8.9235   94.4507    4.8304    2.5743    0.2375   88.3245    4.4036   57.0000 
+2520.5250    8.5000    8.9235   96.0026    4.8913    2.5716    0.2366   88.5582    4.3177   57.0000 
+2520.6250    8.5000    8.9235   99.3753    4.8321    2.5698    0.2353   88.9459    4.2388   57.0000 
+2520.7250    8.5000    8.9072  102.6481    4.6630    2.5634    0.2355   89.4291    4.1191   57.0000 
+2520.8250    8.5000    8.9153  104.0079    4.4175    2.5575    0.2371   89.8888    4.0550   57.0000 
+2520.9250    8.5000    8.9072  105.2678    4.1424    2.5556    0.2399   90.3423    4.1093   57.0000 
+2521.0250    8.5000    8.9072  104.8837    3.8891    2.5580    0.2429   90.8265    4.2575   57.0000 
+2521.1250    8.5000    8.9153  104.4689    3.6987    2.5601    0.2472   91.2842    4.4420   57.0000 
+2521.2250    8.5000    8.8826  105.2141    3.5878    2.5592    0.2509   91.6077    4.5471   57.0000 
+2521.3250    8.5000    8.8826  106.3665    3.5562    2.5570    0.2506   91.6423    4.4929   57.0000 
+2521.4250    8.5000    8.8581  107.0118    3.5964    2.5631    0.2455   91.3949    4.4462   57.0000 
+2521.5250    8.5000    8.8744  106.9043    3.6954    2.5686    0.2408   90.9515    4.4000   57.0000 
+2521.6250    8.5000    8.8581  105.4292    3.8351    2.5773    0.2389   90.5219    4.5080   57.0000 
+2521.7250    8.5000    8.8744  103.1551    3.9862    2.5761    0.2421   90.2934    4.5923   57.0000 
+2521.8250    8.5000    8.8826  101.4726    4.1058    2.5767    0.2459   90.3327    4.7294   57.0000 
+2521.9250    8.5000    8.8990   99.4444    4.1448    2.5741    0.2518   90.6051    4.8736   57.0000 
+2522.0250    8.5000    8.8826   99.0910    4.0748    2.5732    0.2556   91.0066    4.9832   57.0000 
+2522.1250    8.5000    8.9072   98.8144    3.9146    2.5743    0.2570   91.3781    5.0527   57.0000 
+2522.2250    8.5000    8.9235   97.6851    3.7248    2.5728    0.2566   91.5776    5.0074   57.0000 
+2522.3250    8.5000    8.9399   96.6863    3.5653    2.5685    0.2563   91.6520    4.9128   57.0000 
+2522.4250    8.5000    8.9317   94.5890    3.4627    2.5586    0.2573   91.5806    4.7481   57.0000 
+2522.5250    8.5000    8.9072   92.8834    3.4092    2.5522    0.2571   91.4577    4.6149   57.0000 
+2522.6250    8.5000    8.8663   92.6068    3.3784    2.5517    0.2552   91.2929    4.5410   57.0000 
+2522.7250    8.5000    8.8499   94.5429    3.3423    2.5569    0.2553   91.0668    4.6457   57.0000 
+2522.8250    8.5000    8.8826   97.0704    3.2880    2.5611    0.2570   90.9260    4.7891   57.0000 
+2522.9250    8.5000    8.9072   98.9450    3.2301    2.5640    0.2608   90.8653    4.9731   57.0000 
+2523.0250    8.5000    8.9317  101.2114    3.2015    2.5647    0.2599   90.8755    4.9552   57.0000 
+2523.1250    8.5000    8.9399  101.3497    3.2380    2.5674    0.2562   90.8699    4.8889   57.0000 
+2523.2250    8.5000    8.9235  102.6327    3.3725    2.5723    0.2510   90.7367    4.8123   57.0000 
+2523.3250    8.5000    8.9399  104.4304    3.6343    2.5787    0.2488   90.4867    4.8657   57.0000 
+2523.4250    8.5000    8.9235  104.4612    4.0216    2.5851    0.2499   90.1418    5.0315   57.0000 
+2523.5250    8.5000    8.9235  104.1385    4.4407    2.5871    0.2523   89.8714    5.1502   57.0000 
+2523.6250    8.5000    8.8990  101.0962    4.6787    2.5867    0.2538   89.7015    5.1949   57.0000 
+2523.7250    8.5000    8.9072   97.8080    4.5762    2.5839    0.2523   89.7694    5.0891   57.0000 
+2523.8250    8.5000    8.9235   95.5416    4.2335    2.5811    0.2487   89.9587    4.9126   57.0000 
+2523.9250    8.5000    8.9235   94.8041    3.8684    2.5791    0.2475   90.1490    4.8317   57.0000 
+2524.0250    8.5000    8.8826   95.5570    3.5972    2.5761    0.2468   90.2867    4.7502   57.0000 
+2524.1250    8.5000    8.8663   95.8643    3.4260    2.5710    0.2464   90.2475    4.6330   57.0000 
+2524.2250    8.5000    8.8335   95.7644    3.3259    2.5655    0.2425   90.1474    4.3912   57.0000 
+2524.3250    8.5000    8.8172   93.9667    3.2693    2.5671    0.2392   90.0378    4.3172   57.0000 
+2524.4250    8.5000    8.8499   93.0217    3.2354    2.5782    0.2379   89.9648    4.4930   57.0000 
+2524.5250    8.5000    8.8581   92.7912    3.2083    2.5906    0.2390   90.0071    4.7799   57.0000 
+2524.6250    8.5000    8.8826   92.3917    3.1775    2.5938    0.2407   90.2179    4.9018   57.0000 
+2524.7250    8.5000    8.8826   93.9282    3.1415    2.5879    0.2435   90.5918    4.8755   57.0000 
+2524.8250    8.5000    8.8663   94.4968    3.1046    2.5759    0.2478   91.0454    4.7794   57.0000 
+2524.9250    8.5000    8.8663   94.8348    3.0728    2.5624    0.2519   91.3750    4.6429   57.0000 
+2525.0250    8.5000    8.8744   95.8105    3.0559    2.5507    0.2539   91.4990    4.4768   57.0000 
+2525.1250    8.5000    8.8744   95.9104    3.0727    2.5434    0.2525   91.4811    4.2824   57.0000 
+2525.2250    8.5000    8.8663   95.0730    3.1492    2.5440    0.2510   91.4025    4.2455   57.0000 
+2525.3250    8.5000    8.8581   93.8284    3.3077    2.5452    0.2480   91.2194    4.1687   57.0000 
+2525.4250    8.5000    8.8744   92.1151    3.5473    2.5502    0.2441   90.7276    4.1416   57.0000 
+2525.5250    8.5000    8.8826   90.1561    3.8189    2.5524    0.2396   89.8429    4.0361   57.0000 
+2525.6250    8.5000    8.9235   90.3020    4.0236    2.5664    0.2396   88.6327    4.3126   57.0000 
+2525.7250    8.5000    8.9481   91.6234    4.0839    2.5782    0.2441   87.4230    4.6994   57.0000 
+2525.8250    8.5000    8.9399   93.2368    4.0355    2.5934    0.2499   86.4776    5.1963   57.0000 
+2525.9250    8.5000    8.9562   94.4276    3.9736    2.5941    0.2535   85.9781    5.3326   57.0000 
+2526.0250    8.5000    8.9072   94.5352    3.9454    2.5938    0.2541   86.0872    5.3466   57.0000 
+2526.1250    8.5000    8.8826   93.8130    3.9371    2.5889    0.2539   86.7311    5.2418   57.0000 
+2526.2250    8.5000    8.8499   93.3136    3.9260    2.5844    0.2526   87.7985    5.1085   57.0000 
+2526.3250    8.5000    8.8663   93.9974    3.9131    2.5782    0.2513   88.8704    4.9417   57.0000 
+2526.4250    8.5000    8.8744   93.6440    3.9134    2.5709    0.2508   89.6592    4.7764   57.0000 
+2526.5250    8.5000    8.8990   91.9845    3.9364    2.5675    0.2500   89.8832    4.6831   57.0000 
+2526.6250    8.5000    8.9235   88.2354    3.9848    2.5653    0.2462   89.5332    4.5140   57.0000 
+2526.7250    8.5000    8.8990   82.8422    4.0673    2.5633    0.2364   88.7388    4.1453   57.0000 
+2526.8250    8.5000    8.8663   78.9701    4.2023    2.5641    0.2243   87.7321    3.7582   57.0000 
+2526.9250    8.5000    8.8744   77.9099    4.4041    2.5645    0.2158   86.8403    3.4845   57.0000 
+2527.0250    8.5000    8.8581   80.2608    4.6602    2.5704    0.2158   86.3250    3.6020   57.0000 
+2527.1250    8.5000    8.8908   85.0087    4.8914    2.5704    0.2214   86.2679    3.7854   57.0000 
+2527.2250    8.5000    8.9072   89.3647    4.9543    2.5721    0.2278   86.6628    4.0356   57.0000 
+2527.3250    8.5000    8.8990   92.3610    4.7599    2.5736    0.2318   87.4944    4.1987   57.0000 
+2527.4250    8.5000    8.8908   93.3904    4.3789    2.5778    0.2350   88.6026    4.3902   57.0000 
+2527.5250    8.5000    8.9072   92.9449    3.9558    2.5841    0.2362   89.8133    4.5539   57.0000 
+2527.6250    8.5000    8.8908   93.1561    3.5910    2.5832    0.2332   90.9036    4.4374   57.0000 
+2527.7250    8.5000    8.8990   92.7413    3.3187    2.5809    0.2259   91.3765    4.1466   57.0000 
+2527.8250    8.5000    8.9072   93.6325    3.1407    2.5706    0.2176   91.3495    3.6663   57.0000 
+2527.9250    8.5000    8.8990   94.7234    3.0512    2.5651    0.2118   90.6714    3.3608   57.0000 
+2528.0250    8.5000    8.8990   93.7246    3.0428    2.5602    0.2082   89.6245    3.1435   57.0000 
+2528.1250    8.5000    8.9399   93.7016    3.1115    2.5628    0.2051   88.4505    3.0940   57.0000 
+2528.2250    8.5000    8.9317   92.3648    3.2556    2.5646    0.2035   87.3352    3.0759   57.0000 
+2528.3250    8.5000    8.9399   91.3968    3.4637    2.5667    0.2020   86.4571    3.0676   57.0000 
+2528.4250    8.5000    8.9317   91.7156    3.7104    2.5695    0.2008   85.8832    3.0827   57.0000 
+2528.5250    8.5000    8.9153   91.7464    3.9567    2.5786    0.1966   85.3694    3.1265   57.0000 
+2528.6250    8.5000    8.9153   91.9384    4.1610    2.5912    0.1891   84.5153    3.1270   57.0000 
+2528.7250    8.5000    8.9153   90.7246    4.3081    2.6020    0.1811   83.3066    3.0749   57.0000 
+2528.8250    8.5000    8.9235   90.3327    4.4247    2.6071    0.1784   81.8520    3.0891   57.0000 
+2528.9250    8.5000    8.9235   90.5555    4.5449    2.6077    0.1838   80.8265    3.2800   57.0000 
+2529.0250    8.5000    8.9317   92.3379    4.6705    2.6078    0.1946   80.6755    3.6406   57.0000 
+2529.1250    8.5000    8.9399   96.4251    4.7536    2.6042    0.2064   81.4031    3.9647   57.0000 
+2529.2250    8.5000    8.9153   99.7747    4.7155    2.5994    0.2181   82.9469    4.2577   57.0000 
+2529.3250    8.5000    8.9153  102.1410    4.5039    2.5850    0.2272   84.7801    4.2753   57.0000 
+2529.4250    8.5000    8.9153  100.4278    4.1593    2.5685    0.2273   86.7240    3.9465   57.0000 
+2529.5250    8.5000    8.8908   93.8975    3.7952    2.5518    0.2141   88.0219    3.1704   57.0000 
+2529.6250    8.5000    8.9481   84.3172    3.5179    2.5472    0.1862   88.1230    2.1502   57.0000 
+2529.7250    8.5000    8.9971   71.7791    3.3967    2.5563    0.1529   86.4505    1.2222   57.0000 
+2529.8250    8.5000    9.0953   62.0183    3.4850    2.5756    0.1231   82.9923    0.6152   57.0000 
+2529.9250    8.5000    9.1362   57.9158    3.8425    2.5954    0.1080   78.5689    0.5079   57.0000 
+2530.0250    8.5000    9.1853   60.2513    4.5312    2.6110    0.1099   74.0888    0.8831   57.0000 
+2530.1250    8.5000    9.2016   68.9942    5.5303    2.6222    0.1262   70.8393    1.6516   57.0000 
+2530.2250    8.5000    9.1934   80.6488    6.5201    2.6301    0.1509   69.6148    2.6324   57.0000 
+2530.3250    8.5000    9.2180   91.9269    6.8632    2.6322    0.1782   70.4908    3.5827   57.0000 
+2530.4250    8.5000    9.2016   99.8477    6.3396    2.6267    0.2020   73.1260    4.2681   57.0000 
+2530.5250    8.5000    9.2098  104.0271    5.4532    2.6195    0.2177   76.6990    4.6492   57.0000 
+2530.6250    8.5000    9.2425  104.1615    4.6844    2.6095    0.2233   80.5597    4.6336   57.0000 
+2530.7250    8.5000    9.2343  102.0258    4.1792    2.6042    0.2219   83.8801    4.4787   57.0000 
+2530.8250    8.5000    9.2589   99.0142    3.9114    2.5973    0.2163   85.9092    4.1534   57.0000 
+2530.9250    8.5000    9.2916   97.4085    3.8128    2.5960    0.2091   86.2327    3.8913   57.0000 
+2531.0250    8.5000    9.2752   96.7631    3.8226    2.5900    0.2028   85.3490    3.5602   57.0000 
+2531.1250    8.5000    9.2671   94.6888    3.9094    2.5899    0.1963   84.0801    3.3407   57.0000 
+2531.2250    8.5000    9.2752   93.0140    4.0662    2.5915    0.1903   83.2291    3.1711   57.0000 
+2531.3250    8.5000    9.2834   88.8807    4.2784    2.6042    0.1818   82.5949    3.1431   57.0000 
+2531.4250    8.5000    9.2916   84.4709    4.4918    2.6093    0.1739   82.0092    2.9831   57.0000 
+2531.5250    8.5000    9.2998   82.3658    4.6457    2.6048    0.1700   81.0811    2.7619   57.0000 
+2531.6250    8.5000    9.2752   80.5988    4.7435    2.5847    0.1715   79.9607    2.4098   57.0000 
+2531.7250    8.5000    9.2671   80.9138    4.8494    2.5680    0.1759   79.0408    2.2226   57.0000 
+2531.8250    8.5000    9.2671   80.9061    4.9968    2.5649    0.1759   78.5408    2.1599   57.0000 
+2531.9250    8.5000    9.2916   79.6462    5.1374    2.5774    0.1706   78.1225    2.2358   57.0000 
+2532.0250    8.5000    9.2998   78.6013    5.1959    2.5933    0.1638   77.2398    2.3266   57.0000 
+2532.1250    8.5000    9.2834   78.9317    5.1684    2.6055    0.1601   75.6173    2.4468   57.0000 
+2532.2250    8.5000    9.3080   82.1430    5.1238    2.6137    0.1597   73.4949    2.5967   57.0000 
+2532.3250    8.5000    9.2998   89.2572    5.1225    2.6256    0.1614   72.1173    2.8902   57.0000 
+2532.4250    8.5000    9.3407   97.6774    5.1766    2.6352    0.1652   71.9745    3.2090   57.0000 
+2532.5250    8.5000    9.3243  104.0540    5.2632    2.6425    0.1739   73.1633    3.6461   57.0000 
+2532.6250    8.5000    9.3243  107.1347    5.3504    2.6400    0.1856   75.3010    3.9859   57.0000 
+2532.7250    8.5000    9.3161  105.6289    5.4086    2.6355    0.1973   77.4087    4.2860   57.0000 
+2532.8250    8.5000    9.3080  102.0795    5.4149    2.6329    0.2035   79.0179    4.4429   57.0000 
+2532.9250    8.5000    9.3243   97.6620    5.3560    2.6339    0.2045   79.8617    4.4947   57.0000 
+2533.0250    8.5000    9.3407   94.2355    5.2439    2.6335    0.2019   79.7041    4.3996   57.0000 
+2533.1250    8.5000    9.3407   92.9141    5.1180    2.6271    0.1989   79.2276    4.1710   57.0000 
+2533.2250    8.5000    9.3407   92.6376    5.0318    2.6202    0.1935   78.5025    3.8538   57.0000 
+2533.3250    8.5000    9.3570   91.9307    5.0272    2.6179    0.1864   77.7342    3.5713   57.0000 
+2533.4250    8.5000    9.3161   90.6862    5.1143    2.6179    0.1798   76.9490    3.3519   57.0000 
+2533.5250    8.5000    9.2998   87.8282    5.2768    2.6175    0.1769   76.0306    3.2459   57.0000 
+2533.6250    8.5000    9.2916   83.8640    5.4880    2.6139    0.1770   75.1153    3.1772   57.0000 
+2533.7250    8.5000    9.2752   82.8037    5.7151    2.6101    0.1777   74.1724    3.1262   57.0000 
+2533.8250    8.5000    9.2998   84.2174    5.9033    2.5987    0.1806   73.1694    2.9930   57.0000 
+2533.9250    8.5000    9.3243   87.5439    5.9939    2.5876    0.1885   72.2138    3.0331   57.0000 
+2534.0250    8.5000    9.3325   91.7694    5.9765    2.5809    0.2034   71.3653    3.3987   57.0000 
+2534.1250    8.5000    9.3325   95.4571    5.9104    2.5914    0.2189   70.8821    4.1258   57.0000 
+2534.2250    8.5000    9.3325   96.7170    5.8730    2.6020    0.2267   70.7087    4.5980   57.0000 
+2534.3250    8.5000    9.3243   97.5084    5.9073    2.5982    0.2200   70.9995    4.2970   57.0000 
+2534.4250    8.5000    9.3080   98.3074    5.9916    2.5825    0.2061   71.7469    3.5188   57.0000 
+2534.5250    8.5000    9.3243   96.5711    6.0577    2.5692    0.1925   73.1714    2.7993   57.0000 
+2534.6250    8.5000    9.3161   95.1882    6.0459    2.5786    0.1859   74.7796    2.7669   57.0000 
+2534.7250    8.5000    9.3325   92.6913    5.9475    2.5960    0.1803   76.1781    2.9287   57.0000 
+2534.8250    8.5000    9.3570   89.0498    5.7940    2.6138    0.1760   77.0954    3.1432   57.0000 
+2534.9250    8.5000    9.3652   87.4786    5.6447    2.6187    0.1755   77.6301    3.2226   57.0000 
+2535.0250    8.5000    9.3734   86.4492    5.5777    2.6136    0.1869   78.2413    3.5015   57.0000 
+2535.1250    8.5000    9.3979   87.5171    5.6540    2.6030    0.2053   79.1281    3.9022   57.0000 
+2535.2250    8.5000    9.3734   90.9435    5.8530    2.5897    0.2236   80.3117    4.2467   57.0000 
+2535.3250    8.5000    9.3734   95.2996    6.0144    2.5809    0.2324   81.6893    4.3661   57.0000 
+2535.4250    8.5000    9.3816  100.2319    5.9243    2.5768    0.2353   83.0362    4.3800   57.0000 
+2535.5250    8.5000    9.3652  103.6391    5.5709    2.5829    0.2355   83.9898    4.5086   57.0000 
+2535.6250    8.5000    9.3734  106.1782    5.1623    2.5926    0.2379   84.2413    4.7818   57.0000 
+2535.7250    8.5000    9.3816  107.3691    4.8811    2.6045    0.2390   83.9597    5.0579   57.0000 
+2535.8250    8.5000    9.3898  108.7519    4.7756    2.6043    0.2398   83.7520    5.0793   57.0000 
+2535.9250    8.5000    9.3816  109.9965    4.7999    2.5996    0.2354   84.0224    4.8387   57.0000 
+2536.0250    8.5000    9.3734  109.8967    4.8540    2.5858    0.2310   84.6459    4.4148   57.0000 
+2536.1250    8.5000    9.3816  110.1963    4.8384    2.5815    0.2248   85.4658    4.1217   57.0000 
+2536.2250    8.5000    9.3489  109.6124    4.7146    2.5788    0.2230   86.4577    4.0096   57.0000 
+2536.3250    8.5000    9.3407  109.7622    4.5236    2.5837    0.2216   87.7082    4.0611   57.0000 
+2536.4250    8.5000    9.3161  110.8416    4.3372    2.5841    0.2201   88.9526    4.0179   57.0000 
+2536.5250    8.5000    9.3080  110.6073    4.1980    2.5890    0.2141   89.4602    3.9178   57.0000 
+2536.6250    8.5000    9.3161  108.1796    4.1037    2.5948    0.2056   88.9102    3.7487   57.0000 
+2536.7250    8.5000    9.2425  104.5150    4.0369    2.6025    0.1966   87.4209    3.6023   57.0000 
+2536.8250    8.5000    9.1934  100.1666    4.0074    2.6047    0.1880   85.5301    3.3590   57.0000 
+2536.9250    8.5000    9.1444   95.6645    4.0642    2.6072    0.1808   83.4740    3.1697   57.0000 
+2537.0250    8.5000    9.0953   92.2112    4.2717    2.6123    0.1742   81.2495    3.0548   57.0000 
+2537.1250    8.5000    9.0953   87.9012    4.6671    2.6212    0.1692   78.7847    3.0632   57.0000 
+2537.2250    8.5000    9.1198   83.1533    5.2024    2.6248    0.1636   76.6225    2.9485   57.0000 
+2537.3250    8.5000    9.1198   78.9547    5.7443    2.6203    0.1574   75.4372    2.6515   57.0000 
+2537.4250    8.5000    9.1525   76.1160    6.2030    2.6090    0.1515   75.6077    2.2293   57.0000 
+2537.5250    8.5000    9.1444   74.7331    6.6343    2.6029    0.1472   77.1684    1.9651   57.0000 
+2537.6250    8.5000    9.1362   73.6767    7.0800    2.6042    0.1463   78.8020    1.9601   57.0000 
+2537.7250    8.5000    9.1362   73.5154    7.3988    2.6128    0.1479   79.6561    2.1849   57.0000 
+2537.8250    8.5000    9.1444   73.8035    7.3869    2.6219    0.1525   79.0694    2.5218   57.0000 
+2537.9250    8.5000    9.1280   75.9162    7.0828    2.6272    0.1600   77.4173    2.8767   57.0000 
+2538.0250    8.5000    9.1117   79.5809    6.7244    2.6277    0.1698   76.1781    3.2134   57.0000 
+2538.1250    8.5000    9.0953   83.7257    6.4585    2.6187    0.1804   75.8571    3.3887   57.0000 
+2538.2250    8.5000    9.1198   86.9485    6.2644    2.6064    0.1876   76.6122    3.3817   57.0000 
+2538.3250    8.5000    9.1280   88.8999    6.0496    2.5932    0.1906   77.8775    3.2177   57.0000 
+2538.4250    8.5000    9.1280   90.3788    5.7789    2.5864    0.1889   79.1327    3.0245   57.0000 
+2538.5250    8.5000    9.1525   90.5940    5.5087    2.5878    0.1858   80.0918    2.9504   57.0000 
+2538.6250    8.5000    9.1280   91.6081    5.3235    2.5998    0.1820   80.8214    3.0617   57.0000 
+2538.7250    8.5000    9.1117   93.1446    5.2665    2.6120    0.1799   81.1694    3.2364   57.0000 
+2538.8250    8.5000    9.0953   95.8182    5.3160    2.6182    0.1807   81.2903    3.3866   57.0000 
+2538.9250    8.5000    9.0871   99.3215    5.4087    2.6094    0.1851   81.4015    3.3570   57.0000 
+2539.0250    8.5000    9.0708  101.1807    5.4833    2.6026    0.1900   81.5975    3.3850   57.0000 
+2539.1250    8.5000    9.0708  100.3279    5.5197    2.5979    0.1926   81.8434    3.3766   57.0000 
+2539.2250    8.5000    9.0789   96.5173    5.5342    2.6043    0.1915   81.9347    3.4696   57.0000 
+2539.3250    8.5000    9.1117   92.1535    5.5506    2.6075    0.1899   81.6122    3.4809   57.0000 
+2539.4250    8.5000    9.1117   89.6336    5.5779    2.6101    0.1873   80.9673    3.4455   57.0000 
+2539.5250    8.5000    9.1198   90.3097    5.6019    2.6046    0.1866   80.1821    3.3122   57.0000 
+2539.6250    8.5000    9.1198   92.4916    5.6105    2.6008    0.1854   79.6893    3.1955   57.0000 
+2539.7250    8.5000    9.1362   96.9783    5.6196    2.5987    0.1879   79.6403    3.2371   57.0000 
+2539.8250    8.5000    9.1525  101.7569    5.6555    2.6041    0.1922   80.0454    3.4886   57.0000 
+2539.9250    8.5000    9.1444  105.3600    5.7083    2.6073    0.1987   80.5546    3.7686   57.0000 
+2540.0250    8.5000    9.1525  109.0439    5.7244    2.6048    0.2032   80.9842    3.8687   57.0000 
+2540.1250    8.5000    9.1198  108.7366    5.6504    2.6012    0.2030   81.2015    3.7902   57.0000 
+2540.2250    8.5000    9.1198  106.5240    5.4973    2.6084    0.1963   81.2403    3.7091   57.0000 
+2540.3250    8.5000    9.1117  103.6507    5.3354    2.6256    0.1853   81.0750    3.6876   57.0000 
+2540.4250    8.5000    9.1444   99.9361    5.2425    2.6391    0.1755   80.5102    3.6322   57.0000 
+2540.5250    8.5000    9.1117   98.9527    5.2668    2.6407    0.1700   79.5230    3.4787   57.0000 
+2540.6250    8.5000    9.0953   98.7837    5.4200    2.6386    0.1699   78.1949    3.4360   57.0000 
+2540.7250    8.5000    9.0462  100.9156    5.6747    2.6373    0.1719   77.0133    3.4763   57.0000 
+2540.8250    8.5000    9.0053  104.9298    5.9645    2.6383    0.1780   76.5163    3.6986   57.0000 
+2540.9250    8.5000    9.0053  107.7801    6.1991    2.6339    0.1878   77.1005    3.9381   57.0000 
+2541.0250    8.5000    9.0299  111.7366    6.2965    2.6257    0.2022   78.8117    4.2554   57.0000 
+2541.1250    8.5000    9.0544  113.9723    6.2063    2.6151    0.2146   80.8612    4.4558   57.0000 
+2541.2250    8.5000    9.0462  114.2143    5.9184    2.6042    0.2194   82.6189    4.3961   57.0000 
+2541.3250    8.5000    9.0135  114.7214    5.4957    2.5976    0.2149   83.3378    4.1146   57.0000 
+2541.4250    8.5000    8.9808  111.4870    5.0663    2.5896    0.2028   82.9561    3.5501   57.0000 
+2541.5250    8.5000    8.9971  107.0810    4.7453    2.5850    0.1900   81.9265    3.0345   57.0000 
+2541.6250    8.5000    9.0380  103.5815    4.5871    2.5827    0.1787   80.6852    2.6098   57.0000 
+2541.7250    8.5000    9.0626  100.2242    4.6071    2.5903    0.1734   79.6327    2.5847   57.0000 
+2541.8250    8.5000    9.0708  100.5046    4.8017    2.5983    0.1726   78.8087    2.7188   57.0000 
+2541.9250    8.5000    9.0871  101.3190    5.1398    2.5997    0.1769   78.1459    2.8915   57.0000 
+2542.0250    8.5000    9.0871  101.3689    5.5415    2.5921    0.1828   77.8520    2.9352   57.0000 
+2542.1250    8.5000    9.0462  100.4623    5.8767    2.5918    0.1877   77.8694    3.0911   57.0000 
+2542.2250    8.5000    8.9971   98.4495    6.0273    2.6017    0.1910   78.2112    3.3994   57.0000 
+2542.3250    8.5000    8.9890   96.2138    5.9838    2.6182    0.1941   78.6051    3.8335   57.0000 
+2542.4250    8.5000    9.0053   94.2893    5.8518    2.6191    0.1973   78.6980    3.9587   57.0000 
+2542.5250    8.5000    9.0135   93.2445    5.7555    2.6121    0.1980   78.6429    3.8397   57.0000 
+2542.6250    8.5000    9.0217   92.1036    5.7618    2.6048    0.1953   78.1939    3.6058   57.0000 
+2542.7250    8.5000    9.0217   92.0575    5.8770    2.6110    0.1889   77.4240    3.5163   57.0000 
+2542.8250    8.5000    9.0299   90.9781    6.0642    2.6133    0.1801   76.3454    3.2710   57.0000 
+2542.9250    8.5000    9.0626   87.9204    6.2494    2.6020    0.1685   75.0607    2.6582   57.0000 
+2543.0250    8.5000    9.0217   83.4798    6.3803    2.5733    0.1562   74.1852    1.6718   57.0000 
+2543.1250    8.5000    9.0053   79.0623    6.4839    2.5524    0.1440   73.9306    0.8488   57.0000 
+2543.2250    8.5000    9.0053   77.7716    6.6291    2.5511    0.1343   74.4867    0.5006   57.0000 
+2543.3250    8.5000    8.9726   79.8613    6.8113    2.5722    0.1275   75.4311    0.6928   57.0000 
+2543.4250    8.5000    9.0135   85.4696    6.9097    2.5925    0.1273   76.0163    1.0944   57.0000 
+2543.5250    8.5000    9.0135   90.0792    6.7733    2.5997    0.1347   76.0036    1.4854   57.0000 
+2543.6250    8.5000    9.0053   92.8143    6.3984    2.5932    0.1511   75.5505    1.9023   57.0000 
+2543.7250    8.5000    9.0462   94.9270    5.9514    2.5833    0.1691   75.2847    2.3011   57.0000 
+2543.8250    8.5000    9.0053   95.0653    5.6099    2.5744    0.1847   75.8337    2.6444   57.0000 
+2543.9250    8.5000    8.9971   96.4213    5.4465    2.5662    0.1933   77.2296    2.7696   57.0000 
+2544.0250    8.5000    9.0135   97.3739    5.4248    2.5677    0.1995   79.1097    3.0053   57.0000 
+2544.1250    8.5000    9.0053   96.2599    5.4292    2.5800    0.2017   80.7888    3.3241   57.0000 
+2544.2250    8.5000    9.0380   94.0127    5.3301    2.6017    0.1996   81.9163    3.6882   57.0000 
+2544.3250    8.5000    9.0626   89.6221    5.0989    2.6148    0.1900   82.2745    3.6286   57.0000 
+2544.4250    8.5000    9.0626   84.7820    4.8428    2.6208    0.1767   81.6852    3.3063   57.0000 
+2544.5250    8.5000    9.0789   81.8549    4.6922    2.6230    0.1693   80.3475    3.1021   57.0000 
+2544.6250    8.5000    9.1198   80.9714    4.7122    2.6261    0.1730   78.5367    3.2882   57.0000 
+2544.7250    8.5000    9.1117   82.9997    4.9011    2.6280    0.1878   77.1714    3.8209   57.0000 
+2544.8250    8.5000    9.1035   86.8102    5.2228    2.6222    0.2002   76.7923    4.1161   57.0000 
+2544.9250    8.5000    9.1117   91.3507    5.6003    2.6112    0.2065   77.3959    4.1071   57.0000 
+2545.0250    8.5000    9.1035   94.9731    5.8845    2.5981    0.2057   78.5551    3.8199   57.0000 
+2545.1250    8.5000    9.1198   97.3125    5.8876    2.5910    0.2045   79.8332    3.6370   57.0000 
+2545.2250    8.5000    9.1444   99.0948    5.5737    2.5900    0.2021   80.8352    3.5381   57.0000 
+2545.3250    8.5000    9.1444   98.0654    5.1466    2.5904    0.1986   81.6153    3.4277   57.0000 
+2545.4250    8.5000    9.1607   96.8976    4.8366    2.5891    0.1953   81.8398    3.2921   57.0000 
+2545.5250    8.5000    9.1525   96.5634    4.7392    2.5903    0.1955   81.7531    3.3226   57.0000 
+2545.6250    8.5000    9.1362   97.0397    4.8231    2.5931    0.2000   81.6495    3.5267   57.0000 
+2545.7250    8.5000    9.1444   99.6365    4.9747    2.5951    0.2044   81.7689    3.7154   57.0000 
+2545.8250    8.5000    9.1198  102.1410    5.0421    2.5942    0.2072   82.1786    3.7922   57.0000 
+2545.9250    8.5000    9.1525  103.5085    4.9443    2.6010    0.2107   82.8633    4.0458   57.0000 
+2546.0250    8.5000    9.1280  103.6161    4.7171    2.6104    0.2186   83.8097    4.4951   57.0000 
+2546.1250    8.5000    9.1280  103.1705    4.4373    2.6135    0.2292   85.0745    4.9104   57.0000 
+2546.2250    8.5000    9.1280  103.2281    4.1550    2.6058    0.2353   86.5413    4.9569   57.0000 
+2546.3250    8.5000    9.1035  103.2358    3.9024    2.5991    0.2359   87.7357    4.8455   57.0000 
+2546.4250    8.5000    9.0953  103.4970    3.7112    2.6012    0.2317   88.3388    4.7467   57.0000 
+2546.5250    8.5000    9.0871  103.8658    3.6027    2.6039    0.2270   88.1184    4.6453   57.0000 
+2546.6250    8.5000    9.0953  104.6724    3.5808    2.6065    0.2207   87.3561    4.4851   57.0000 
+2546.7250    8.5000    9.1117  104.8415    3.6322    2.6060    0.2136   86.4148    4.2385   57.0000 
+2546.8250    8.5000    9.1362  103.3357    3.7339    2.6031    0.2084   85.4719    4.0070   57.0000 
+2546.9250    8.5000    9.1444  100.0014    3.8538    2.5955    0.2058   84.4883    3.7706   57.0000 
+2547.0250    8.5000    9.1607   94.9270    3.9596    2.5872    0.2069   83.4378    3.6399   57.0000 
+2547.1250    8.5000    9.1117   91.7195    4.0390    2.5854    0.2077   82.4980    3.6293   57.0000 
+2547.2250    8.5000    9.1362   91.7195    4.1097    2.5865    0.2081   82.1245    3.6661   57.0000 
+2547.3250    8.5000    9.1525   94.6543    4.1969    2.5878    0.2081   82.3878    3.6925   57.0000 
+2547.4250    8.5000    9.1362   98.1230    4.3038    2.5865    0.2082   83.0689    3.6706   57.0000 
+2547.5250    8.5000    9.1607  100.2203    4.4031    2.5837    0.2083   83.6321    3.6181   57.0000 
+2547.6250    8.5000    9.1771  100.0744    4.4644    2.5823    0.2058   83.9311    3.5072   57.0000 
+2547.7250    8.5000    9.2016   98.3995    4.4878    2.5822    0.2027   83.8541    3.4013   57.0000 
+2547.8250    8.5000    9.2343   97.9770    4.5034    2.5852    0.1977   83.5878    3.2928   57.0000 
+2547.9250    8.5000    9.2262   97.9655    4.5447    2.5860    0.1923   82.9801    3.1294   57.0000 
+2548.0250    8.5000    9.2180   98.8067    4.6321    2.5887    0.1857   82.1638    2.9637   57.0000 
+2548.1250    8.5000    9.2262  100.6198    4.7709    2.5916    0.1828   81.5097    2.9258   57.0000 
+2548.2250    8.5000    9.2671  102.3984    4.9463    2.6003    0.1842   81.3842    3.1464   57.0000 
+2548.3250    8.5000    9.2916  105.5944    5.1215    2.6043    0.1919   81.6617    3.4844   57.0000 
+2548.4250    8.5000    9.2916  107.8992    5.2411    2.6043    0.2009   81.9719    3.7849   57.0000 
+2548.5250    8.5000    9.2671  107.0502    5.2503    2.5975    0.2094   81.8801    3.9314   57.0000 
+2548.6250    8.5000    9.2507  103.8466    5.1350    2.5922    0.2108   81.3184    3.8689   57.0000 
+2548.7250    8.5000    9.2343   97.9424    4.9545    2.5911    0.2067   80.5102    3.7113   57.0000 
+2548.8250    8.5000    9.2343   92.0229    4.8048    2.5968    0.1988   79.6633    3.5620   57.0000 
+2548.9250    8.5000    9.2507   88.9729    4.7617    2.6059    0.1917   78.9939    3.5070   57.0000 
+2549.0250    8.5000    9.2507   88.2661    4.8513    2.6125    0.1871   78.6066    3.4868   57.0000 
+2549.1250    8.5000    9.2262   90.3404    5.0597    2.6139    0.1852   78.6607    3.4521   57.0000 
+2549.2250    8.5000    9.2589   95.4264    5.3197    2.6116    0.1891   78.9648    3.5357   57.0000 
+2549.3250    8.5000    9.2671  101.9028    5.4991    2.6103    0.1958   79.5806    3.7324   57.0000 
+2549.4250    8.5000    9.2916  108.4946    5.4604    2.6093    0.2044   80.4510    3.9999   57.0000 
+2549.5250    8.5000    9.3243  113.1772    5.2079    2.6123    0.2102   81.4832    4.2508   57.0000 
+2549.6250    8.5000    9.3325  114.9365    4.8943    2.6159    0.2138   82.6607    4.4425   57.0000 
+2549.7250    8.5000    9.3407  114.4371    4.6555    2.6244    0.2153   83.5837    4.6632   57.0000 
+2549.8250    8.5000    9.2998  112.7008    4.5264    2.6283    0.2158   84.0561    4.7574   57.0000 
+2549.9250    8.5000    9.2916  110.6342    4.4797    2.6298    0.2168   84.0449    4.8204   57.0000 
+2550.0250    8.5000    9.2916  108.1757    4.4856    2.6247    0.2179   83.6577    4.7573   57.0000 
+2550.1250    8.5000    9.3080  104.8107    4.5274    2.6185    0.2193   83.3031    4.6803   57.0000 
+2550.2250    8.5000    9.3407  100.6544    4.6060    2.6124    0.2168   82.9367    4.4761   57.0000 
+2550.3250    8.5000    9.3489   96.9437    4.7328    2.6052    0.2092   82.5107    4.0783   57.0000 
+2550.4250    8.5000    9.3816   92.8796    4.9360    2.5999    0.1953   81.8735    3.5095   57.0000 
+2550.5250    8.5000    9.3816   88.0625    5.2517    2.6002    0.1771   80.7204    2.9081   57.0000 
+2550.6250    8.5000    9.3489   82.6847    5.7083    2.6123    0.1556   79.1296    2.4324   57.0000 
+2550.7250    8.5000    9.3161   74.3336    6.2862    2.6297    0.1327   76.9082    2.0186   57.0000 
+2550.8250    8.5000    9.2834   65.0529    6.9274    2.6356    0.1119   74.4250    1.4428   57.0000 
+2550.9250    8.5000    9.2752   58.9414    7.6690    2.6267    0.0987   72.3000    0.8247   57.0000 
+2551.0250    8.5000    9.2916   57.4279    8.5977    2.6068    0.1003   71.3276    0.4790   57.0000 
+2551.1250    8.5000    9.3652   62.7520    9.3900    2.5947    0.1198   71.7995    0.8879   57.0000 
+2551.2250    8.5000    9.3816   73.4924    9.0559    2.5836    0.1515   73.2709    1.7209   57.0000 
+2551.3250    8.5000    9.3816   84.0944    7.4581    2.5789    0.1829   75.3546    2.6742   57.0000 
+2551.4250    8.5000    9.3898   90.8552    5.7843    2.5751    0.2051   77.9301    3.3379   57.0000 
+2551.5250    8.5000    9.3489   93.9206    4.6920    2.5805    0.2164   80.7923    3.8240   57.0000 
+2551.6250    8.5000    9.3407   93.0563    4.1643    2.5872    0.2214   83.3163    4.1245   57.0000 
+2551.7250    8.5000    9.3816   90.2214    4.0498    2.5909    0.2237   84.4985    4.2758   57.0000 
+2551.8250    8.5000    9.3979   88.7847    4.2273    2.5931    0.2275   84.4505    4.4446   57.0000 
+2551.9250    8.5000    9.3898   87.5670    4.5686    2.5903    0.2335   83.7974    4.5891   57.0000 
+2552.0250    8.5000    9.3979   87.7283    4.9152    2.5851    0.2387   83.5352    4.6592   57.0000 
+2552.1250    8.5000    9.3734   88.6887    5.1121    2.5766    0.2409   84.0602    4.5619   57.0000 
+2552.2250    8.5000    9.3734   89.3186    5.0864    2.5699    0.2415   85.2133    4.4476   57.0000 
+2552.3250    8.5000    9.3816   90.5632    4.8645    2.5679    0.2431   86.6750    4.4599   57.0000 
+2552.4250    8.5000    9.4388   92.0037    4.5271    2.5623    0.2450   88.0495    4.4121   57.0000 
+2552.5250    8.5000    9.4470   94.4929    4.1603    2.5612    0.2447   89.2842    4.3793   57.0000 
+2552.6250    8.5000    9.4634   96.3521    3.8266    2.5578    0.2431   89.9265    4.2581   57.0000 
+2552.7250    8.5000    9.4470   96.9168    3.5588    2.5613    0.2411   90.1071    4.2606   57.0000 
+2552.8250    8.5000    9.4143   95.6568    3.3638    2.5627    0.2418   89.8872    4.3128   57.0000 
+2552.9250    8.5000    9.4143   92.7451    3.2357    2.5651    0.2431   89.6092    4.4051   57.0000 
+2553.0250    8.5000    9.4225   90.8629    3.1653    2.5672    0.2469   89.5122    4.5742   57.0000 
+2553.1250    8.5000    9.4470   89.9640    3.1430    2.5675    0.2445   89.4699    4.5012   57.0000 
+2553.2250    8.5000    9.4552   89.9793    3.1635    2.5695    0.2381   89.4658    4.3268   57.0000 
+2553.3250    8.5000    9.4716   91.0626    3.2359    2.5702    0.2266   89.3765    3.9582   57.0000 
+2553.4250    8.5000    9.4961   91.5159    3.3920    2.5731    0.2189   89.3459    3.7567   57.0000 
+2553.5250    8.5000    9.4879   92.1459    3.6783    2.5786    0.2149   89.3801    3.7340   57.0000 
+2553.6250    8.5000    9.4797   93.8937    4.1122    2.5833    0.2132   89.3786    3.7743   57.0000 
+2553.7250    8.5000    9.4797   95.4917    4.5845    2.5898    0.2139   89.2969    3.9237   57.0000 
+2553.8250    8.5000    9.4797   97.0051    4.7876    2.5896    0.2145   89.1699    3.9422   57.0000 
+2553.9250    8.5000    9.4879   97.1895    4.5170    2.5913    0.2162   89.4255    4.0316   57.0000 
+2554.0250    8.5000    9.4961   96.3291    4.0047    2.5902    0.2145   91.5204    3.9541   57.0000 
+2554.1250    8.5000    9.4879   95.5301    3.5777    2.5976    0.2120   94.3046    4.0191   57.0000 
+2554.2250    8.5000    9.4879   94.9078    3.3458    2.6055    0.2085   97.1163    4.0617   57.0000 
+2554.3250    8.5000    9.4879   94.6850    3.2842    2.6107    0.2087   97.5459    4.1693   57.0000 
+2554.4250    8.5000    9.4716   93.8668    3.3226    2.6061    0.2112   94.8490    4.1610   57.0000 
+2554.5250    8.5000    9.4634   92.4724    3.3830    2.5986    0.2171   91.7592    4.2066   57.0000 
+2554.6250    8.5000    9.4797   92.0882    3.4186    2.5953    0.2216   88.9352    4.2948   57.0000 
+2554.7250    8.5000    9.4879   92.8027    3.4406    2.5929    0.2256   87.9199    4.3796   57.0000 
+2554.8250    8.5000    9.4797   94.8962    3.4949    2.5898    0.2272   87.7194    4.3700   57.0000 
+2554.9250    8.5000    9.4552   97.9463    3.6272    2.5834    0.2275   87.6332    4.2506   57.0000 
+2555.0250    8.5000    9.4225  100.5430    3.8592    2.5826    0.2255   87.7107    4.1683   57.0000 
+2555.1250    8.5000    9.4225  102.6096    4.1637    2.5825    0.2219   88.1337    4.0457   57.0000 
+2555.2250    8.5000    9.4225  103.0476    4.4607    2.5835    0.2191   88.8347    3.9728   57.0000 
+2555.3250    8.5000    9.4388  102.7134    4.6751    2.5814    0.2193   89.5740    3.9358   57.0000 
+2555.4250    8.5000    9.4552  100.7351    4.7979    2.5807    0.2228   89.9321    4.0414   57.0000 
+2555.5250    8.5000    9.4552   98.4072    4.8760    2.5781    0.2259   89.6469    4.0909   57.0000 
+2555.6250    8.5000    9.4307   97.6659    4.9607    2.5760    0.2250   88.7872    4.0178   57.0000 
+2555.7250    8.5000    9.4143   96.3752    5.0641    2.5754    0.2214   87.4679    3.8877   57.0000 
+2555.8250    8.5000    9.3734   95.9987    5.1478    2.5823    0.2172   85.9378    3.8857   57.0000 
+2555.9250    8.5000    9.3407   95.4609    5.1572    2.5881    0.2140   84.3561    3.8948   57.0000 
+2556.0250    8.5000    9.3325   94.1510    5.0799    2.5880    0.2080   82.9587    3.6934   57.0000 
+2556.1250    8.5000    9.2671   94.1510    4.9518    2.5838    0.2010   81.8403    3.3754   57.0000 
+2556.2250    8.5000    9.2425   94.6466    4.8353    2.5816    0.1955   81.0102    3.1467   57.0000 
+2556.3250    8.5000    9.1853   94.7541    4.7808    2.5871    0.1935   80.3107    3.1899   57.0000 
+2556.4250    8.5000    9.1362   94.4430    4.8170    2.5938    0.1942   79.6230    3.3487   57.0000 
+2556.5250    8.5000    9.1198   93.2137    4.9402    2.5991    0.1934   79.0117    3.4279   57.0000 
+2556.6250    8.5000    9.0708   92.5070    5.1190    2.5983    0.1947   78.5709    3.4560   57.0000 
+2556.7250    8.5000    9.0462   93.5057    5.2801    2.5916    0.1989   78.4066    3.4625   57.0000 
+2556.8250    8.5000    9.0299   95.0192    5.3270    2.5833    0.2089   78.5791    3.6270   57.0000 
+2556.9250    8.5000    9.0053   97.9540    5.2063    2.5772    0.2201   79.0577    3.8826   57.0000 
+2557.0250    8.5000    9.0135  100.2780    4.9581    2.5767    0.2284   79.8607    4.1466   57.0000 
+2557.1250    8.5000    8.9890  101.7415    4.6793    2.5773    0.2321   80.9352    4.2822   57.0000 
+2557.2250    8.5000    8.9971  104.5034    4.4449    2.5758    0.2318   82.1862    4.2434   57.0000 
+2557.3250    8.5000    8.9971  105.8709    4.2747    2.5708    0.2332   83.3403    4.1895   57.0000 
+2557.4250    8.5000    9.0217  106.0630    4.1500    2.5662    0.2357   84.2469    4.1816   57.0000 
+2557.5250    8.5000    9.0053  106.3089    4.0481    2.5624    0.2396   84.9490    4.2338   57.0000 
+2557.6250    8.5000    9.0053  104.1769    3.9607    2.5625    0.2404   85.5337    4.2629   57.0000 
+2557.7250    8.5000    9.0135  100.9118    3.8924    2.5633    0.2421   86.0883    4.3353   57.0000 
+2557.8250    8.5000    8.9971   98.7952    3.8489    2.5644    0.2435   86.6097    4.4045   57.0000 
+2557.9250    8.5000    9.0053   95.8912    3.8331    2.5646    0.2459   86.9546    4.4890   57.0000 
+2558.0250    8.5000    9.0053   93.4788    3.8504    2.5654    0.2456   87.1372    4.4934   57.0000 
+2558.1250    8.5000    8.9971   92.4493    3.9151    2.5701    0.2439   87.1275    4.5325   57.0000 
+2558.2250    8.5000    8.9726   90.7284    4.0485    2.5756    0.2409   87.0709    4.5426   57.0000 
+2558.3250    8.5000    8.9971   88.2239    4.2555    2.5850    0.2345   86.9995    4.5175   57.0000 
+2558.4250    8.5000    9.0053   86.7795    4.5087    2.5928    0.2262   86.4408    4.3979   57.0000 
+2558.5250    8.5000    8.9890   85.6463    4.7735    2.5979    0.2164   85.2367    4.1729   57.0000 
+2558.6250    8.5000    8.9726   84.9088    5.0445    2.5982    0.2109   83.3250    3.9948   57.0000 
+2558.7250    8.5000    8.9153   87.0446    5.3311    2.5958    0.2092   81.6199    3.8889   57.0000 
+2558.8250    8.5000    8.8663   88.7501    5.5890    2.5967    0.2131   80.7393    4.0374   57.0000 
+2558.9250    8.5000    8.8254   90.7860    5.6961    2.5923    0.2214   80.7980    4.2276   57.0000 
+2559.0250    8.5000    8.8335   94.2125    5.5503    2.5872    0.2318   81.3403    4.4726   57.0000 
+2559.1250    8.5000    8.8663   96.4405    5.2035    2.5751    0.2417   81.9230    4.5583   57.0000 
+2559.2250    8.5000    8.8581   98.0922    4.8100    2.5700    0.2494   82.6388    4.7124   57.0000 
+2559.3250    8.5000    8.8908   99.6096    4.4817    2.5642    0.2565   83.6648    4.8360   57.0000 
+2559.4250    8.5000    8.8990   99.1793    4.2512    2.5637    0.2625   85.0985    5.0226   57.0000 
+2559.5250    8.5000    8.8826   98.8451    4.1043    2.5575    0.2654   86.6000    4.9965   57.0000 
+2559.6250    8.5000    8.8744  100.0129    4.0108    2.5540    0.2672   87.8541    4.9854   57.0000 
+2559.7250    8.5000    8.8581  101.1845    3.9442    2.5461    0.2712   88.8872    4.9611   57.0000 
+2559.8250    8.5000    8.8744  104.3344    3.8906    2.5454    0.2760   89.7276    5.1069   57.0000 
+2559.9250    8.5000    8.8826  107.1309    3.8430    2.5447    0.2775   90.6434    5.1430   57.0000 
+2560.0250    8.5000    8.8744  108.6597    3.7931    2.5464    0.2734   91.6459    5.0433   57.0000 
+2560.1250    8.5000    8.8581  109.2513    3.7297    2.5406    0.2700   92.5663    4.8115   57.0000 
+2560.2250    8.5000    8.8335  108.7519    3.6490    2.5300    0.2688   93.3281    4.5615   57.0000 
+2560.3250    8.5000    8.8335  108.4600    3.5683    2.5237    0.2693   94.1337    4.4526   57.0000 
+2560.4250    8.5000    8.8254  107.9453    3.5186    2.5246    0.2681   94.6480    4.4294   57.0000 
+2560.5250    8.5000    8.8417  107.1194    3.5221    2.5349    0.2630   94.6143    4.4664   57.0000 
+2560.6250    8.5000    8.8499  105.8325    3.5765    2.5460    0.2547   93.7153    4.4104   57.0000 
+2560.7250    8.5000    8.8335  103.5892    3.6611    2.5553    0.2445   91.4699    4.2554   57.0000 
+2560.8250    8.5000    8.8663  101.5456    3.7528    2.5598    0.2373   89.7760    4.1041   57.0000 
+2560.9250    8.5000    8.8581  100.7082    3.8435    2.5591    0.2332   88.8342    3.9574   57.0000 
+2561.0250    8.5000    8.8826  100.3548    3.9449    2.5592    0.2305   88.5551    3.8667   57.0000 
+2561.1250    8.5000    8.8744  100.7312    4.0744    2.5606    0.2281   87.9036    3.8157   57.0000 
+2561.2250    8.5000    8.8663  100.8618    4.2343    2.5664    0.2255   85.7821    3.8444   57.0000 
+2561.3250    8.5000    8.8663   99.8477    4.3960    2.5729    0.2258   83.0633    3.9856   57.0000 
+2561.4250    8.5000    8.8744   97.7158    4.5180    2.5808    0.2266   81.1112    4.1675   57.0000 
+2561.5250    8.5000    8.8744   95.5723    4.5831    2.5867    0.2293   80.4071    4.3764   57.0000 
+2561.6250    8.5000    8.8744   95.0345    4.6086    2.5895    0.2308   80.9673    4.4828   57.0000 
+2561.7250    8.5000    8.8581   96.0256    4.6187    2.5846    0.2325   81.6184    4.4426   57.0000 
+2561.8250    8.5000    8.8663   97.5621    4.6205    2.5775    0.2332   82.1454    4.3254   57.0000 
+2561.9250    8.5000    8.8744   99.7747    4.6038    2.5752    0.2348   82.4250    4.3306   57.0000 
+2562.0250    8.5000    8.8744  100.9271    4.5530    2.5789    0.2346   82.6551    4.3977   57.0000 
+2562.1250    8.5000    8.8990  101.0193    4.4653    2.5856    0.2325   82.9383    4.4635   57.0000 
+2562.2250    8.5000    8.9235  101.6954    4.3599    2.5850    0.2276   83.2372    4.2865   57.0000 
+2562.3250    8.5000    8.9153  100.7889    4.2746    2.5858    0.2220   83.5092    4.1169   57.0000 
+2562.4250    8.5000    8.9317   98.8836    4.2451    2.5832    0.2202   83.5418    4.0047   57.0000 
+2562.5250    8.5000    8.8990   95.9795    4.2841    2.5835    0.2223   83.4520    4.0788   57.0000 
+2562.6250    8.5000    8.8908   92.8911    4.3703    2.5792    0.2283   83.2888    4.1952   57.0000 
+2562.7250    8.5000    8.8663   91.0396    4.4647    2.5775    0.2338   83.2592    4.3441   57.0000 
+2562.8250    8.5000    8.8499   91.5159    4.5299    2.5766    0.2375   83.4393    4.4490   57.0000 
+2562.9250    8.5000    8.8908   93.7746    4.5459    2.5775    0.2383   83.7893    4.4940   57.0000 
+2563.0250    8.5000    8.8744   95.7106    4.5177    2.5777    0.2368   84.4102    4.4471   57.0000 
+2563.1250    8.5000    8.9072   97.2932    4.4730    2.5825    0.2349   85.1225    4.4799   57.0000 
+2563.2250    8.5000    8.9317   96.0371    4.4432    2.5907    0.2339   85.7143    4.6085   57.0000 
+2563.3250    8.5000    8.9644   94.5774    4.4482    2.6002    0.2353   85.9704    4.8452   57.0000 
+2563.4250    8.5000    8.9644   93.6709    4.4894    2.6036    0.2375   85.7480    4.9876   57.0000 
+2563.5250    8.5000    8.9644   92.2880    4.5530    2.6043    0.2396   85.2735    5.0736   57.0000 
+2563.6250    8.5000    8.9399   93.8245    4.6176    2.6009    0.2404   84.8066    5.0318   57.0000 
+2563.7250    8.5000    8.9399   95.3918    4.6625    2.5958    0.2421   84.4959    4.9858   57.0000 
+2563.8250    8.5000    8.9235   96.5135    4.6810    2.5875    0.2453   84.4816    4.9267   57.0000 
+2563.9250    8.5000    8.9072   98.8951    4.6783    2.5787    0.2498   84.7459    4.8988   57.0000 
+2564.0250    8.5000    8.8826   99.6518    4.6677    2.5747    0.2534   85.3026    4.9411   57.0000 
+2564.1250    8.5000    8.8990  100.2856    4.6655    2.5775    0.2557   86.1250    5.0749   57.0000 
+2564.2250    8.5000    8.9072  102.3523    4.6807    2.5856    0.2561   86.9056    5.2494   57.0000 
+2564.3250    8.5000    8.9235  104.2115    4.6953    2.5943    0.2574   87.4643    5.4654   57.0000 
+2564.4250    8.5000    8.9562  106.8466    4.6863    2.5987    0.2582   87.6689    5.5798   57.0000 
+2564.5250    8.5000    8.9481  108.8825    4.6576    2.6022    0.2609   87.6077    5.7404   57.0000 
+2564.6250    8.5000    8.9644  109.0516    4.6356    2.5974    0.2622   87.4934    5.6868   57.0000 
+2564.7250    8.5000    8.9726  108.1143    4.6354    2.5879    0.2648   87.4179    5.5837   57.0000 
+2564.8250    8.5000    8.9726  105.7173    4.6481    2.5732    0.2651   87.4485    5.2997   57.0000 
+2564.9250    8.5000    8.9562  104.0924    4.6398    2.5675    0.2649   87.5709    5.1816   57.0000 
+2565.0250    8.5000    8.9235  102.6096    4.5718    2.5714    0.2633   87.6311    5.2047   57.0000 
+2565.1250    8.5000    8.9072  101.8606    4.4398    2.5831    0.2618   87.5832    5.3885   57.0000 
+2565.2250    8.5000    8.9153  102.1602    4.2829    2.5925    0.2609   87.3577    5.5464   57.0000 
+2565.3250    8.5000    8.9072  101.8222    4.1478    2.5993    0.2613   86.9786    5.6966   57.0000 
+2565.4250    8.5000    8.9072  102.8056    4.0508    2.6041    0.2662   86.6026    5.9558   57.0000 
+2565.5250    8.5000    8.9235  103.8734    3.9799    2.6085    0.2694   86.1974    6.1511   57.0000 
+2565.6250    8.5000    8.9153  104.9068    3.9162    2.6090    0.2742   85.9240    6.3203   57.0000 
+2565.7250    8.5000    8.9235  106.4740    3.8541    2.6043    0.2733   85.7781    6.1969   57.0000 
+2565.8250    8.5000    8.9153  106.5355    3.8017    2.5960    0.2759   85.8801    6.1185   57.0000 
+2565.9250    8.5000    8.9153  105.8479    3.7775    2.5866    0.2755   86.1985    5.9132   57.0000 
+2566.0250    8.5000    8.9153  104.9874    3.8014    2.5820    0.2751   86.6781    5.8092   57.0000 
+2566.1250    8.5000    8.9153  103.1282    3.8894    2.5808    0.2691   87.2515    5.5852   57.0000 
+2566.2250    8.5000    8.9235  101.6685    4.0457    2.5835    0.2612   87.8526    5.3774   57.0000 
+2566.3250    8.5000    8.9562  100.4239    4.2592    2.5815    0.2564   88.4301    5.1752   57.0000 
+2566.4250    8.5000    8.9481   98.7376    4.5007    2.5802    0.2552   88.8617    5.1100   57.0000 
+2566.5250    8.5000    8.9399   97.3009    4.7235    2.5772    0.2563   88.9740    5.0883   57.0000 
+2566.6250    8.5000    8.9399   96.1639    4.8795    2.5773    0.2551   88.4801    5.0507   57.0000 
+2566.7250    8.5000    8.9317   95.1190    4.9430    2.5765    0.2546   87.4592    5.0182   57.0000 
+2566.8250    8.5000    8.9726   94.0742    4.9167    2.5729    0.2558   86.0694    4.9856   57.0000 
+2566.9250    8.5000    8.9726   93.0447    4.8225    2.5699    0.2590   84.8888    5.0303   57.0000 
+2567.0250    8.5000    8.9890   92.1766    4.6936    2.5664    0.2626   84.2709    5.0814   57.0000 
+2567.1250    8.5000    9.0053   92.0537    4.5677    2.5684    0.2654   84.1403    5.2153   57.0000 
+2567.2250    8.5000    8.9890   93.3290    4.4761    2.5690    0.2704   84.4454    5.3931   57.0000 
+2567.3250    8.5000    9.0217   95.9795    4.4407    2.5701    0.2753   84.8730    5.5796   57.0000 
+2567.4250    8.5000    9.0626   98.8836    4.4717    2.5682    0.2791   86.0699    5.6661   57.0000 
+2567.5250    8.5000    9.0871  101.1884    4.5587    2.5664    0.2776   89.3158    5.5824   57.0000 
+2567.6250    8.5000    9.1198  102.2793    4.6718    2.5641    0.2745   93.8321    5.4312   57.0000 
+2567.7250    8.5000    9.1280  101.7722    4.7746    2.5617    0.2742   98.1275    5.3735   57.0000 
+2567.8250    8.5000    9.0871   99.9899    4.8351    2.5607    0.2779   99.1097    5.4760   57.0000 
+2567.9250    8.5000    9.0789   96.8092    4.8331    2.5565    0.2823   96.1566    5.5403   57.0000 
+2568.0250    8.5000    9.0871   93.1369    4.7661    2.5543    0.2837   92.2750    5.5444   57.0000 
+2568.1250    8.5000    9.0708   90.2636    4.6567    2.5525    0.2839   89.0883    5.5135   57.0000 
+2568.2250    8.5000    9.0789   88.6195    4.5528    2.5557    0.2873   87.8847    5.6900   57.0000 
+2568.3250    8.5000    9.0871   89.6183    4.5085    2.5568    0.2925   87.9969    5.8872   57.0000 
+2568.4250    8.5000    9.0953   91.9538    4.5551    2.5561    0.2998   88.3204    6.1147   57.0000 
+2568.5250    8.5000    9.0789   94.1280    4.6533    2.5558    0.3028   88.9071    6.2099   57.0000 
+2568.6250    8.5000    9.0789   94.8655    4.7184    2.5611    0.3042   89.7673    6.3607   57.0000 
+2568.7250    8.5000    9.0462   93.5672    4.7035    2.5708    0.3008   90.6189    6.4434   57.0000 
+2568.8250    8.5000    9.0544   91.3238    4.6318    2.5812    0.2979   91.2281    6.5540   57.0000 
+2568.9250    8.5000    9.0871   88.8193    4.5339    2.5892    0.2952   91.4918    6.6253   57.0000 
+2569.0250    8.5000    9.0626   88.1278    4.4309    2.5890    0.2956   91.4112    6.6337   57.0000 
+2569.1250    8.5000    9.0380   88.5120    4.3521    2.5818    0.2957   90.9587    6.4943   57.0000 
+2569.2250    8.5000    9.0217   89.7873    4.3403    2.5670    0.2943   89.9791    6.1493   57.0000 
+2569.3250    8.5000    9.0053   91.1932    4.4337    2.5581    0.2891   88.6316    5.7986   57.0000 
+2569.4250    8.5000    9.0053   91.4775    4.6469    2.5546    0.2794   86.9434    5.4046   57.0000 
+2569.5250    8.5000    9.0053   92.3302    4.9592    2.5585    0.2667   85.1954    5.0613   57.0000 
+2569.6250    8.5000    9.0217   93.4058    5.3111    2.5606    0.2520   83.6704    4.6136   57.0000 
+2569.7250    8.5000    9.0217   94.8502    5.6195    2.5610    0.2398   82.6332    4.2114   57.0000 
+2569.8250    8.5000    9.0380   96.8784    5.8122    2.5620    0.2317   82.3842    3.9627   57.0000 
+2569.9250    8.5000    9.0380   97.7158    5.8713    2.5652    0.2288   82.7347    3.9326   57.0000 
+2570.0250    8.5000    9.0135   96.3483    5.8451    2.5721    0.2290   83.2444    4.0757   57.0000 
+2570.1250    8.5000    9.0217   93.9052    5.8077    2.5745    0.2272   83.4173    4.0654   57.0000 
+2570.2250    8.5000    9.0135   90.6170    5.8158    2.5827    0.2222   82.7939    4.0618   57.0000 
+2570.3250    8.5000    9.0053   87.0215    5.8955    2.5925    0.2141   81.4959    3.9870   57.0000 
+2570.4250    8.5000    9.0380   85.3928    6.0418    2.6077    0.2063   79.7413    4.0298   57.0000 
+2570.5250    8.5000    9.0380   85.2545    6.2178    2.6079    0.2001   77.9357    3.8287   57.0000 
+2570.6250    8.5000    9.0380   85.4235    6.3655    2.5960    0.1964   76.4061    3.4649   57.0000 
+2570.7250    8.5000    9.0462   85.9229    6.4389    2.5756    0.1972   75.3056    3.0839   57.0000 
+2570.8250    8.5000    9.0217   85.1546    6.4457    2.5606    0.1997   74.6964    2.8679   57.0000 
+2570.9250    8.5000    9.0217   82.9881    6.4283    2.5562    0.2024   74.6878    2.8715   57.0000 
+2571.0250    8.5000    9.0135   81.8972    6.4092    2.5588    0.2022   75.1827    2.9147   57.0000 
+2571.1250    8.5000    8.9971   81.8357    6.3477    2.5645    0.2019   76.1755    3.0196   57.0000 
+2571.2250    8.5000    8.9890   84.1559    6.1803    2.5643    0.2040   77.6112    3.0869   57.0000 
+2571.3250    8.5000    9.0135   88.4582    5.8974    2.5566    0.2097   79.3949    3.1219   57.0000 
+2571.4250    8.5000    9.0217   93.2368    5.5734    2.5498    0.2193   81.5510    3.3045   57.0000 
+2571.5250    8.5000    9.0299   99.2293    5.2913    2.5484    0.2289   83.8102    3.5980   57.0000 
+2571.6250    8.5000    9.0299  103.7928    5.0857    2.5572    0.2387   86.0189    4.1009   57.0000 
+2571.7250    8.5000    9.0380  107.3191    4.9421    2.5676    0.2471   88.0429    4.5910   57.0000 
+2571.8250    8.5000    9.0544  109.4703    4.8310    2.5765    0.2571   89.5704    5.1016   57.0000 
+2571.9250    8.5000    9.0462  108.8403    4.7221    2.5793    0.2654   90.5796    5.4322   57.0000 
+2572.0250    8.5000    9.0708  108.2257    4.5995    2.5746    0.2713   91.0531    5.5349   57.0000 
+2572.1250    8.5000    9.0626  107.3499    4.4675    2.5665    0.2709   91.2648    5.3599   57.0000 
+2572.2250    8.5000    9.0299  105.5214    4.3432    2.5622    0.2683   91.3143    5.1892   57.0000 
+2572.3250    8.5000    9.0462  104.5418    4.2424    2.5615    0.2640   91.7031    5.0301   57.0000 
+2572.4250    8.5000    9.0217  102.2678    4.1750    2.5626    0.2623   93.7122    4.9970   57.0000 
+2572.5250    8.5000    9.0380   99.8554    4.1371    2.5612    0.2638   96.1602    5.0174   57.0000 
+2572.6250    8.5000    9.0217   99.0872    4.1014    2.5573    0.2684   98.8087    5.0928   57.0000 
+2572.7250    8.5000    9.0217   97.7580    4.0288    2.5522    0.2751   99.3148    5.2139   57.0000 
+2572.8250    8.5000    8.9808   98.4495    3.8945    2.5431    0.2800   98.9444    5.1952   57.0000 
+2572.9250    8.5000    8.8990  100.2626    3.7024    2.5382    0.2838  100.1760    5.2242   57.0000 
+2573.0250    8.5000    8.8663  101.2767    3.4706    2.5359    0.2853  101.9653    5.2271   57.0000 
+2573.1250    8.5000    8.8254  102.4790    3.2165    2.5375    0.2878  104.7041    5.3420   57.0000 
+2573.2250    8.5000    8.8417  102.3254    2.9671    2.5369    0.2886  104.0612    5.3583   57.0000 
+2573.3250    8.5000    8.8499  100.8964    2.7633    2.5397    0.2871  102.2883    5.3636   57.0000 
+2573.4250    8.5000    8.8826   99.9438    2.6344    2.5432    0.2832  100.2475    5.3039   57.0000 
+2573.5250    8.5000    8.8744   99.9438    2.5829    2.5493    0.2815   99.1964    5.3689   57.0000 
+2573.6250    8.5000    8.8581  101.5341    2.5930    2.5468    0.2841   99.1980    5.4037   57.0000 
+2573.7250    8.5000    8.8663  104.2153    2.6447    2.5466    0.2891   99.0025    5.5709   57.0000 
+2573.8250    8.5000    8.8908  106.1821    2.7172    2.5495    0.2903   98.6643    5.6671   57.0000 
+2573.9250    8.5000    8.9072  108.0413    2.7899    2.5643    0.2875   98.1495    5.8701   57.0000 
+2574.0250    8.5000    8.9153  108.4177    2.8429    2.5777    0.2801   97.4776    5.8914   57.0000 
+2574.1250    8.5000    8.9235  107.0502    2.8584    2.5880    0.2749   96.7806    5.9224   57.0000 
+2574.2250    8.5000    8.8663  105.7288    2.8308    2.5867    0.2750   96.2225    5.9005   57.0000 
+2574.3250    8.5000    8.8663  103.1321    2.7759    2.5808    0.2790   95.9526    5.9142   57.0000 
+2574.4250    8.5000    8.8908   99.9130    2.7207    2.5741    0.2857   96.1597    6.0051   57.0000 
+2574.5250    8.5000    8.8990   97.2241    2.6890    2.5752    0.2896   96.7372    6.1575   57.0000 
+2574.6250    8.5000    8.8908   94.5198    2.6909    2.5797    0.2934   97.7061    6.3733   57.0000 
+2574.7250    8.5000    8.9153   92.5223    2.7146    2.5761    0.2932   98.6724    6.2947   57.0000 
+2574.8250    8.5000    8.8744   90.7015    2.7341    2.5644    0.2928   98.5439    6.0477   57.0000 
+2574.9250    8.5000    8.8335   87.9665    2.7462    2.5562    0.2928   96.1316    5.8826   57.0000 
+2575.0250    8.5000    8.8335   85.7385    2.7939    2.5630    0.2916   91.4541    5.9803   57.0000 
+2575.1250    8.5000    8.8581   83.3953    2.9292    2.5745    0.2887   84.9388    6.1147   57.0000 
+2575.2250    8.5000    8.8744   81.8434    3.1608    2.5790    0.2836   79.2883    6.0324   57.0000 
+2575.3250    8.5000    8.8826   82.5733    3.4284    2.5724    0.2832   75.3097    5.8864   57.0000 
+2575.4250    8.5000    8.8663   85.1393    3.6280    2.5607    0.2839   73.4755    5.6757   57.0000 
+2575.5250    8.5000    8.8663   88.2431    3.7072    2.5521    0.2867   74.3092    5.5994   57.0000 
+2575.6250    8.5000    8.8417   92.0460    3.7210    2.5516    0.2875   76.9025    5.6151   57.0000 
+2575.7250    8.5000    8.8663   95.5877    3.7469    2.5613    0.2893   81.2801    5.8673   57.0000 
+2575.8250    8.5000    8.8826   95.6645    3.8026    2.5720    0.2873   85.9985    6.0156   57.0000 
+2575.9250    8.5000    8.8826   95.8720    3.8653    2.5772    0.2830   89.4230    5.9760   57.0000 
+2576.0250    8.5000    8.9072   95.6722    3.9206    2.5790    0.2757   91.4179    5.7689   57.0000 
+2576.1250    8.5000    8.8826   95.3803    3.9698    2.5805    0.2718   91.7525    5.6696   57.0000 
+2576.2250    8.5000    8.8417   97.8003    4.0093    2.5847    0.2688   91.5816    5.6557   57.0000 
+2576.3250    8.5000    8.8090   99.6749    4.0173    2.5863    0.2687   91.2291    5.6815   57.0000 
+2576.4250    8.5000    8.7926  101.0654    3.9628    2.5883    0.2706   91.1209    5.7865   57.0000 
+2576.5250    8.5000    8.8008  101.4112    3.8267    2.5861    0.2763   91.6372    5.9296   57.0000 
+2576.6250    8.5000    8.8172  100.7504    3.6212    2.5837    0.2829   92.7679    6.1051   57.0000 
+2576.7250    8.5000    8.8172  100.8426    3.3854    2.5770    0.2846   94.3546    6.0286   57.0000 
+2576.8250    8.5000    8.8499  101.3036    3.1678    2.5719    0.2825   95.8964    5.8540   57.0000 
+2576.9250    8.5000    8.8417  102.0795    3.0072    2.5683    0.2804   97.0638    5.7113   57.0000 
+2577.0250    8.5000    8.8744  102.2562    2.9201    2.5689    0.2813   97.7087    5.7555   57.0000 
+2577.1250    8.5000    8.8499  101.1884    2.8933    2.5704    0.2832   97.8469    5.8474   57.0000 
+2577.2250    8.5000    8.8744  100.4585    2.8897    2.5695    0.2812   97.7066    5.7637   57.0000 
+2577.3250    8.5000    8.8826  101.3574    2.8783    2.5670    0.2807   97.4020    5.6966   57.0000 
+2577.4250    8.5000    8.8744  102.0795    2.8600    2.5661    0.2830   97.2566    5.7547   57.0000 
+2577.5250    8.5000    8.9072  104.0463    2.8580    2.5661    0.2881   98.8719    5.9278   57.0000 
+2577.6250    8.5000    8.8826  104.7685    2.8991    2.5657    0.2874  102.5602    5.8943   57.0000 
+2577.7250    8.5000    8.8826  103.3472    2.9991    2.5607    0.2817  107.5602    5.6058   57.0000 
+2577.8250    8.5000    8.8826  104.0540    3.1538    2.5533    0.2759  110.8403    5.2641   57.0000 
+2577.9250    8.5000    8.8499  104.8914    3.3348    2.5437    0.2714  109.8510    4.9211   57.0000 
+2578.0250    8.5000    8.8663  106.8044    3.4912    2.5386    0.2682  104.9806    4.7097   57.0000 
+2578.1250    8.5000    8.8826  109.1706    3.5662    2.5344    0.2614   99.5617    4.4011   57.0000 
+2578.2250    8.5000    8.8744  110.2769    3.5437    2.5365    0.2572   96.0842    4.3025   57.0000 
+2578.3250    8.5000    8.8663  109.9543    3.4705    2.5357    0.2542   94.6801    4.1898   57.0000 
+2578.4250    8.5000    8.8744  108.8134    3.4144    2.5394    0.2546   94.4107    4.2740   57.0000 
+2578.5250    8.5000    8.8663  107.8454    3.4250    2.5422    0.2524   93.7372    4.2567   57.0000 
+2578.6250    8.5000    8.8335  104.8031    3.5274    2.5491    0.2498   92.7173    4.3085   57.0000 
+2578.7250    8.5000    8.8417  101.5763    3.7217    2.5619    0.2479   91.4786    4.4999   57.0000 
+2578.8250    8.5000    8.8254   98.6185    3.9755    2.5777    0.2516   90.2153    4.9399   57.0000 
+2578.9250    8.5000    8.8417   95.3918    4.2182    2.5925    0.2571   89.1612    5.4180   57.0000 
+2579.0250    8.5000    8.8581   94.3930    4.3548    2.5970    0.2601   88.3694    5.6112   57.0000 
+2579.1250    8.5000    8.8417   94.6235    4.3317    2.5918    0.2578   87.7296    5.4288   57.0000 
+2579.2250    8.5000    8.8335   95.5416    4.1891    2.5811    0.2523   87.1837    5.0309   57.0000 
+2579.3250    8.5000    8.8090   96.7401    4.0264    2.5683    0.2479   86.6668    4.6304   57.0000 
+2579.4250    8.5000    8.7926   96.7862    3.9252    2.5606    0.2446   86.2908    4.3664   57.0000 
+2579.5250    8.5000    8.7845   96.1869    3.9125    2.5598    0.2452   86.1189    4.3688   57.0000 
+2579.6250    8.5000    8.8090   94.4814    3.9546    2.5685    0.2489   86.1301    4.6651   57.0000 
+2579.7250    8.5000    8.8417   92.8527    3.9908    2.5793    0.2535   86.3913    5.0367   57.0000 
+2579.8250    8.5000    8.8581   91.4775    3.9967    2.5854    0.2537   86.7883    5.1654   57.0000 
+2579.9250    8.5000    8.8744   89.3878    4.0120    2.5805    0.2475   87.2806    4.8592   57.0000 
+2580.0250    8.5000    8.8254   88.6963    4.0951    2.5673    0.2421   87.6281    4.4171   57.0000 
+2580.1250    8.5000    8.7926   88.9729    4.2679    2.5526    0.2406   87.6750    4.0739   57.0000 
+2580.2250    8.5000    8.7681   91.2009    4.4867    2.5478    0.2446   87.6199    4.1084   57.0000 
+2580.3250    8.5000    8.8172   95.9949    4.6542    2.5533    0.2476   89.0628    4.3193   57.0000 
+2580.4250    8.5000    8.8581   99.9284    4.6811    2.5689    0.2500   92.6638    4.7110   57.0000 
+2580.5250    8.5000    8.9153  103.2166    4.5623    2.5795    0.2517   98.4168    4.9795   57.0000 
+2580.6250    8.5000    8.9153  104.1001    4.3768    2.5839    0.2549  104.7684    5.1744   57.0000 
+2580.7250    8.5000    8.9072  102.2409    4.2094    2.5754    0.2563  109.1026    5.0533   57.0000 
+2580.8250    8.5000    8.8826  100.4739    4.0987    2.5649    0.2555  111.2026    4.8134   57.0000 
+2580.9250    8.5000    8.8417   96.9706    4.0452    2.5568    0.2500  109.7449    4.4677   57.0000 
+2581.0250    8.5000    8.8744   95.3572    4.0409    2.5605    0.2440  105.7857    4.3441   57.0000 
+2581.1250    8.5000    8.8990   94.6389    4.0826    2.5738    0.2381   99.7995    4.4117   57.0000 
+2581.2250    8.5000    8.9072   92.7720    4.1741    2.5877    0.2367   93.3209    4.6435   57.0000 
+2581.3250    8.5000    8.9399   93.1100    4.3152    2.5911    0.2365   88.9939    4.7058   57.0000 
+2581.4250    8.5000    8.9072   91.6964    4.4891    2.5828    0.2378   86.8969    4.5841   57.0000 
+2581.5250    8.5000    8.8826   90.8667    4.6614    2.5707    0.2374   86.7969    4.3264   57.0000 
+2581.6250    8.5000    8.8826   91.3891    4.8051    2.5679    0.2386   87.1010    4.3133   57.0000 
+2581.7250    8.5000    8.8663   90.0831    4.9336    2.5772    0.2409   87.1796    4.5740   57.0000 
+2581.8250    8.5000    8.8826   90.3059    5.0802    2.5928    0.2447   87.0352    5.0129   57.0000 
+2581.9250    8.5000    8.8826   90.6324    5.2500    2.6054    0.2456   86.5857    5.2949   57.0000 
+2582.0250    8.5000    8.8581   90.7015    5.4042    2.6060    0.2425   85.8622    5.2048   57.0000 
+2582.1250    8.5000    8.8744   91.4391    5.5036    2.6005    0.2359   85.0352    4.8749   57.0000 
+2582.2250    8.5000    8.8417   90.7553    5.5405    2.5929    0.2280   84.1566    4.4572   57.0000 
+2582.3250    8.5000    8.8581   90.2098    5.5417    2.5879    0.2220   83.4597    4.1567   57.0000 
+2582.4250    8.5000    8.8499   90.7092    5.5346    2.5853    0.2178   83.0087    3.9655   57.0000 
+2582.5250    8.5000    8.8499   92.0690    5.5258    2.5834    0.2171   82.5908    3.9056   57.0000 
+2582.6250    8.5000    8.9072   93.9513    5.5052    2.5847    0.2160   82.1474    3.8923   57.0000 
+2582.7250    8.5000    8.9235   93.9820    5.4627    2.5834    0.2131   81.0796    3.7707   57.0000 
+2582.8250    8.5000    8.9562   91.3699    5.3998    2.5794    0.2080   79.3903    3.5205   57.0000 
+2582.9250    8.5000    8.9562   87.2443    5.3387    2.5845    0.2002   77.0270    3.3617   57.0000 
+2583.0250    8.5000    8.9481   83.3031    5.3263    2.6087    0.1919   74.2393    3.5713   57.0000 
+2583.1250    8.5000    8.9481   81.4285    5.4129    2.6451    0.1809   71.9765    3.9332   57.0000 
+2583.2250    8.5000    8.9481   81.9433    5.6225    2.6758    0.1727   70.4025    4.2713   57.0000 
+2583.3250    8.5000    8.9317   83.5643    5.9073    2.6824    0.1684   69.7689    4.2597   57.0000 
+2583.4250    8.5000    8.8908   85.3467    6.1436    2.6787    0.1691   70.0821    4.2120   57.0000 
+2583.5250    8.5000    8.8581   86.4376    6.2181    2.6711    0.1719   71.1270    4.1508   57.0000 
+2583.6250    8.5000    8.8417   88.2354    6.1500    2.6682    0.1727   72.7923    4.1199   57.0000 
+2583.7250    8.5000    8.8581   91.0703    6.0485    2.6596    0.1747   74.7480    4.0171   57.0000 
+2583.8250    8.5000    8.8908   94.3201    5.9873    2.6486    0.1791   76.5622    3.9427   57.0000 
+2583.9250    8.5000    8.9072   97.3009    5.9559    2.6392    0.1869   77.8163    4.0133   57.0000 
+2584.0250    8.5000    8.8908   96.3636    5.9097    2.6308    0.1930   78.2061    4.0506   57.0000 
+2584.1250    8.5000    8.8744   92.3840    5.8321    2.6132    0.1963   77.8372    3.8076   57.0000 
+2584.2250    8.5000    8.8417   87.6822    5.7404    2.5946    0.1962   77.1653    3.4310   57.0000 
+2584.3250    8.5000    8.8254   82.2429    5.6538    2.5909    0.1957   76.7796    3.3420   57.0000 
+2584.4250    8.5000    8.8254   79.8459    5.5839    2.6101    0.1937   76.9245    3.6580   57.0000 
+2584.5250    8.5000    8.8254   79.6692    5.5474    2.6368    0.1932   76.9862    4.1744   57.0000 
+2584.6250    8.5000    8.8417   79.5232    5.5752    2.6498    0.1953   76.6332    4.5066   57.0000 
+2584.7250    8.5000    8.8826   80.9215    5.7040    2.6486    0.2012   75.8969    4.6779   57.0000 
+2584.8250    8.5000    8.8826   81.8818    5.9425    2.6376    0.2071   75.0964    4.6566   57.0000 
+2584.9250    8.5000    8.9072   83.6565    6.2281    2.6278    0.2087   75.0699    4.5113   57.0000 
+2585.0250    8.5000    8.9235   85.3621    6.4180    2.6170    0.2064   75.6842    4.2206   57.0000 
+2585.1250    8.5000    8.9153   86.1918    6.3635    2.6077    0.2044   76.8893    3.9668   57.0000 
+2585.2250    8.5000    8.9072   86.3454    6.0597    2.6020    0.2055   78.3179    3.8906   57.0000 
+2585.3250    8.5000    8.9153   84.4171    5.6640    2.6005    0.2136   79.3230    4.1297   57.0000 
+2585.4250    8.5000    8.9153   81.8972    5.3489    2.6039    0.2270   79.7791    4.6429   57.0000 
+2585.5250    8.5000    8.9399   79.6308    5.1919    2.6082    0.2476   79.5102    5.4190   57.0000 
+2585.6250    8.5000    8.9726   79.2083    5.1801    2.6062    0.2666   78.9342    6.0119   57.0000 
+2585.7250    8.5000    8.9562   81.2903    5.2482    2.5943    0.2811   78.5301    6.2568   57.0000 
+2585.8250    8.5000    8.9481   84.4863    5.3042    2.5699    0.2869   78.9286    5.9605   57.0000 
+2585.9250    8.5000    8.9235   87.8513    5.2504    2.5510    0.2922   80.3857    5.7610   57.0000 
+2586.0250    8.5000    8.8990   90.0485    5.0412    2.5410    0.2965   82.4684    5.7045   57.0000 
+2586.1250    8.5000    8.8744   90.6170    4.7332    2.5455    0.2983   84.6250    5.8539   57.0000 
+2586.2250    8.5000    8.8908   91.8309    4.4486    2.5529    0.2908   85.9602    5.7522   57.0000 
+2586.3250    8.5000    8.8990   93.4980    4.2871    2.5595    0.2778   86.4286    5.4512   57.0000 
+2586.4250    8.5000    8.9235   95.0653    4.2923    2.5640    0.2641   86.2337    5.0822   57.0000 
+2586.5250    8.5000    8.9235   96.7401    4.4429    2.5647    0.2545   85.6745    4.7795   57.0000 
+2586.6250    8.5000    8.9072   97.0935    4.6471    2.5612    0.2479   85.2153    4.4860   57.0000 
+2586.7250    8.5000    8.9072   95.5877    4.7730    2.5578    0.2411   84.9939    4.1935   57.0000 
+2586.8250    8.5000    8.8908   92.4532    4.7563    2.5567    0.2347   85.0541    3.9599   57.0000 
+2586.9250    8.5000    8.9235   88.7194    4.6504    2.5649    0.2295   85.4816    3.9487   57.0000 
+2587.0250    8.5000    8.9153   85.3544    4.5564    2.5661    0.2273   86.0189    3.8987   57.0000 
+2587.1250    8.5000    8.9644   84.5439    4.5430    2.5649    0.2254   86.4929    3.8117   57.0000 
+2587.2250    8.5000    8.9317   86.6643    4.6321    2.5540    0.2257   86.7418    3.6043   57.0000 
+2587.3250    8.5000    8.8990   90.1215    4.7966    2.5500    0.2289   86.5796    3.6317   57.0000 
+2587.4250    8.5000    8.8908   93.1100    4.9603    2.5473    0.2340   86.2051    3.7461   57.0000 
+2587.5250    8.5000    8.8499   94.9001    5.0357    2.5511    0.2367   85.8122    3.9122   57.0000 
+2587.6250    8.5000    8.8826   95.8066    4.9903    2.5537    0.2368   85.5571    3.9669   57.0000 
+2587.7250    8.5000    8.8990   94.9539    4.8684    2.5583    0.2359   85.5311    4.0287   57.0000 
+2587.8250    8.5000    8.9399   96.2753    4.7396    2.5585    0.2349   85.5969    4.0015   57.0000 
+2587.9250    8.5000    8.9971   98.4610    4.6581    2.5570    0.2319   85.5878    3.8706   57.0000 
+2588.0250    8.5000    8.9971  100.1666    4.6450    2.5541    0.2279   85.3974    3.6779   57.0000 
+2588.1250    8.5000    8.9644  103.6852    4.6919    2.5576    0.2244   84.9908    3.6306   57.0000 
+2588.2250    8.5000    8.9644  103.6545    4.7560    2.5676    0.2227   84.3480    3.7750   57.0000 
+2588.3250    8.5000    8.9399  100.0590    4.7808    2.5803    0.2194   83.5602    3.9177   57.0000 
+2588.4250    8.5000    8.9481   96.3022    4.7390    2.5960    0.2141   82.6658    4.0574   57.0000 
+2588.5250    8.5000    8.9399   90.7937    4.6669    2.6138    0.2051   81.9056    4.1122   57.0000 
+2588.6250    8.5000    8.9235   87.0446    4.6290    2.6273    0.1970   81.2026    4.1113   57.0000 
+2588.7250    8.5000    8.9235   87.2366    4.6593    2.6230    0.1906   80.3694    3.8156   57.0000 
+2588.8250    8.5000    8.9399   86.5759    4.7411    2.6011    0.1888   79.3245    3.3164   57.0000 
+2588.9250    8.5000    8.9399   87.0369    4.8297    2.5780    0.1902   77.9653    2.8995   57.0000 
+2589.0250    8.5000    8.9399   87.7053    4.9057    2.5673    0.1919   76.7806    2.7436   57.0000 
+2589.1250    8.5000    8.9481   87.1521    5.0002    2.5713    0.1923   76.0847    2.8357   57.0000 
+2589.2250    8.5000    8.9562   88.8423    5.1560    2.5805    0.1919   75.9158    3.0069   57.0000 
+2589.3250    8.5000    8.9481   90.5786    5.3628    2.5874    0.1937   76.2801    3.2064   57.0000 
+2589.4250    8.5000    8.9399   92.4378    5.5607    2.5918    0.1992   76.8985    3.4772   57.0000 
+2589.5250    8.5000    8.9235   94.1049    5.6968    2.5923    0.2040   77.6235    3.6471   57.0000 
+2589.6250    8.5000    8.9399   94.4122    5.7648    2.5935    0.2071   78.3097    3.7714   57.0000 
+2589.7250    8.5000    8.9153   95.0115    5.7768    2.5880    0.2048   78.7031    3.5871   57.0000 
+2589.8250    8.5000    8.9072   95.6261    5.7251    2.5790    0.2030   78.9975    3.3480   57.0000 
+2589.9250    8.5000    8.8990   96.1793    5.6018    2.5642    0.2006   79.2225    2.9707   57.0000 
+2590.0250    8.5000    8.8908   96.7247    5.4301    2.5555    0.2009   79.6184    2.8068   57.0000 
+2590.1250    8.5000    8.8990   96.6479    5.2747    2.5527    0.2016   80.1281    2.7744   57.0000 
+2590.2250    8.5000    8.9072   96.3713    5.1904    2.5585    0.2032   80.4592    2.9423   57.0000 
+2590.3250    8.5000    8.8826   96.2254    5.1824    2.5632    0.2033   80.5117    3.0393   57.0000 
+2590.4250    8.5000    8.8990   96.5019    5.2087    2.5687    0.2011   80.1888    3.0792   57.0000 
+2590.5250    8.5000    8.8990   97.1319    5.2224    2.5773    0.1961   79.7000    3.0817   57.0000 
+2590.6250    8.5000    8.8990   97.2856    5.2080    2.5894    0.1908   79.2867    3.1485   57.0000 
+2590.7250    8.5000    8.9317   96.7017    5.1874    2.6033    0.1870   79.1311    3.3005   57.0000 
+2590.8250    8.5000    8.9317   95.0883    5.1909    2.6081    0.1889   79.3449    3.4582   57.0000 
+2590.9250    8.5000    8.9644   93.1523    5.2159    2.6074    0.1948   79.9393    3.6432   57.0000 
+2591.0250    8.5000    8.9808   92.2457    5.2109    2.5990    0.2047   80.8974    3.8031   57.0000 
+2591.1250    8.5000    8.9481   92.6068    5.1088    2.5898    0.2134   82.0577    3.9085   57.0000 
+2591.2250    8.5000    8.9562   93.7976    4.8871    2.5840    0.2217   83.2760    4.0717   57.0000 
+2591.3250    8.5000    8.9317   94.5121    4.5957    2.5822    0.2264   84.3260    4.1909   57.0000 
+2591.4250    8.5000    8.8990   94.2432    4.3129    2.5860    0.2302   84.8520    4.3943   57.0000 
+2591.5250    8.5000    8.8990   93.5518    4.0930    2.5864    0.2300   84.8112    4.3951   57.0000 
+2591.6250    8.5000    8.8990   92.9679    3.9510    2.5906    0.2297   84.2097    4.4701   57.0000 
+2591.7250    8.5000    8.8990   93.9359    3.8851    2.5957    0.2258   83.3689    4.4420   57.0000 
+2591.8250    8.5000    8.9153   95.5493    3.8964    2.6061    0.2224   82.7964    4.5349   57.0000 
+2591.9250    8.5000    8.9481   98.7453    3.9777    2.6079    0.2176   82.5102    4.4117   57.0000 
+2592.0250    8.5000    8.9562  101.6109    4.0949    2.6051    0.2158   82.6235    4.2956   57.0000 
+2592.1250    8.5000    8.9808  102.7556    4.1919    2.5940    0.2159   82.8418    4.0765   57.0000 
+2592.2250    8.5000    8.9644  103.4394    4.2363    2.5878    0.2178   83.0092    4.0176   57.0000 
+2592.3250    8.5000    8.9481  101.6570    4.2500    2.5834    0.2191   83.0102    3.9727   57.0000 
+2592.4250    8.5000    8.9317   99.9438    4.2918    2.5879    0.2184   82.6301    4.0390   57.0000 
+2592.5250    8.5000    8.9399   98.5148    4.4087    2.5903    0.2149   81.9883    3.9685   57.0000 
+2592.6250    8.5000    8.9399   97.0858    4.5979    2.5921    0.2106   81.1719    3.8630   57.0000 
+2592.7250    8.5000    8.9644   95.9334    4.7971    2.5861    0.2076   80.5255    3.6404   57.0000 
+2592.8250    8.5000    8.9808   96.3176    4.9220    2.5822    0.2090   80.2745    3.6103   57.0000 
+2592.9250    8.5000    8.9890   98.4841    4.9307    2.5774    0.2123   80.4592    3.6242   57.0000 
+2593.0250    8.5000    9.0053  100.7889    4.8429    2.5786    0.2183   81.0505    3.8483   57.0000 
+2593.1250    8.5000    8.9890  104.3997    4.7031    2.5767    0.2254   81.7480    4.0491   57.0000 
+2593.2250    8.5000    8.9644  105.8671    4.5448    2.5781    0.2327   82.4796    4.3186   57.0000 
+2593.3250    8.5000    8.9562  104.9759    4.3884    2.5811    0.2365   83.1510    4.5058   57.0000 
+2593.4250    8.5000    8.9317  104.1923    4.2462    2.5875    0.2355   83.7867    4.5995   57.0000 
+2593.5250    8.5000    8.9644  102.2716    4.1273    2.5893    0.2339   84.3592    4.5818   57.0000 
+2593.6250    8.5000    8.9562  101.2882    4.0381    2.5861    0.2317   84.7225    4.4437   57.0000 
+2593.7250    8.5000    8.9726  101.4726    3.9770    2.5867    0.2316   84.9531    4.4529   57.0000 
+2593.8250    8.5000    9.0053  101.7185    3.9358    2.5928    0.2306   85.0755    4.5425   57.0000 
+2593.9250    8.5000    8.9890  102.6250    3.9058    2.6004    0.2311   85.2153    4.7103   57.0000 
+2594.0250    8.5000    8.9726  102.6711    3.8845    2.5992    0.2319   85.4643    4.7133   57.0000 
+2594.1250    8.5000    8.9481  102.1180    3.8740    2.5953    0.2344   85.8153    4.7196   57.0000 
+2594.2250    8.5000    8.9317  101.6186    3.8719    2.5891    0.2358   86.2347    4.6403   57.0000 
+2594.3250    8.5000    8.9072  100.3433    3.8651    2.5886    0.2374   86.5847    4.6858   57.0000 
+2594.4250    8.5000    8.8990   99.7133    3.8373    2.5870    0.2346   86.7245    4.5602   57.0000 
+2594.5250    8.5000    8.9072   98.8528    3.7888    2.5900    0.2306   86.5122    4.4849   57.0000 
+2594.6250    8.5000    8.9072   96.0563    3.7458    2.5914    0.2197   85.9189    4.1501   57.0000 
+2594.7250    8.5000    8.9317   91.6772    3.7464    2.5930    0.2065   84.8592    3.7451   57.0000 
+2594.8250    8.5000    8.9562   85.0548    3.8217    2.5969    0.1907   83.3934    3.2930   57.0000 
+2594.9250    8.5000    8.9562   79.3081    3.9899    2.6021    0.1777   81.4403    2.9664   57.0000 
+2595.0250    8.5000    8.9399   76.7344    4.2624    2.6142    0.1712   79.1811    2.9892   57.0000 
+2595.1250    8.5000    8.9153   79.1468    4.6426    2.6218    0.1729   77.0658    3.2006   57.0000 
+2595.2250    8.5000    8.8990   85.2776    5.0962    2.6251    0.1817   75.5689    3.5612   57.0000 
+2595.3250    8.5000    8.9072   91.0549    5.4976    2.6207    0.1952   74.9122    3.9189   57.0000 
+2595.4250    8.5000    8.9072   95.0422    5.6555    2.6140    0.2054   75.1663    4.1249   57.0000 
+2595.5250    8.5000    8.9153   94.4891    5.5148    2.6081    0.2112   76.2480    4.2031   57.0000 
+2595.6250    8.5000    8.9153   92.1228    5.2554    2.6050    0.2076   77.7347    4.0201   57.0000 
+2595.7250    8.5000    8.9399   89.3417    5.0861    2.6045    0.2016   79.1985    3.8105   57.0000 
+2595.8250    8.5000    8.9235   86.4376    5.0927    2.6102    0.1928   79.9429    3.6303   57.0000 
+2595.9250    8.5000    8.9235   85.0548    5.2701    2.6172    0.1849   79.8816    3.5079   57.0000 
+2596.0250    8.5000    8.9235   84.5477    5.5749    2.6208    0.1788   79.3362    3.3772   57.0000 
+2596.1250    8.5000    8.9072   86.1764    5.9340    2.6155    0.1778   78.8423    3.2382   57.0000 
+2596.2250    8.5000    8.8908   88.7501    6.2122    2.6017    0.1833   78.6515    3.1432   57.0000 
+2596.3250    8.5000    8.8581   92.3226    6.2370    2.5896    0.1923   78.7454    3.2028   57.0000 
+2596.4250    8.5000    8.8908   95.8259    5.9598    2.5797    0.2024   79.1959    3.3397   57.0000 
+2596.5250    8.5000    8.8908   97.5352    5.5440    2.5784    0.2092   80.2342    3.5411   57.0000 
+2596.6250    8.5000    8.9235   98.9028    5.1906    2.5800    0.2112   81.4500    3.6382   57.0000 
+2596.7250    8.5000    8.9153   99.0180    4.9797    2.5867    0.2088   82.4776    3.6952   57.0000 
+2596.8250    8.5000    8.8826   98.8490    4.8869    2.5918    0.2067   82.9541    3.7275   57.0000 
+2596.9250    8.5000    8.8826   99.2101    4.8488    2.5947    0.2079   82.8005    3.8225   57.0000 
+2597.0250    8.5000    8.8663   98.8259    4.8112    2.5933    0.2105   82.6168    3.8837   57.0000 
+2597.1250    8.5000    8.8663   98.2805    4.7455    2.5892    0.2139   82.2939    3.9158   57.0000 
+2597.2250    8.5000    8.8826   96.6978    4.6532    2.5899    0.2158   81.9510    3.9904   57.0000 
+2597.3250    8.5000    8.8581   94.1203    4.5534    2.5947    0.2189   81.8760    4.1899   57.0000 
+2597.4250    8.5000    8.8663   92.9986    4.4665    2.6015    0.2216   82.3806    4.4162   57.0000 
+2597.5250    8.5000    8.8663   92.6068    4.4018    2.6037    0.2250   83.3811    4.5715   57.0000 
+2597.6250    8.5000    8.8826   94.1126    4.3541    2.6013    0.2273   84.4796    4.6023   57.0000 
+2597.7250    8.5000    8.9235   97.3854    4.3164    2.5998    0.2283   84.9434    4.6076   57.0000 
+2597.8250    8.5000    8.9153  100.1051    4.2877    2.5965    0.2284   84.7173    4.5418   57.0000 
+2597.9250    8.5000    8.9317  103.3357    4.2726    2.5936    0.2284   84.1908    4.4849   57.0000 
+2598.0250    8.5000    8.9481  105.5483    4.2716    2.5903    0.2288   83.7883    4.4334   57.0000 
+2598.1250    8.5000    8.9562  105.6712    4.2803    2.5883    0.2310   83.7607    4.4662   57.0000 
+2598.2250    8.5000    8.9399  105.3639    4.2920    2.5845    0.2323   83.9796    4.4320   57.0000 
+2598.3250    8.5000    8.9317  102.3446    4.2959    2.5791    0.2359   84.1663    4.4466   57.0000 
+2598.4250    8.5000    8.9072   98.1038    4.2798    2.5795    0.2362   84.0423    4.4650   57.0000 
+2598.5250    8.5000    8.8908   94.6543    4.2455    2.5863    0.2365   83.5230    4.6110   57.0000 
+2598.6250    8.5000    8.9072   89.8103    4.2235    2.5956    0.2314   82.7862    4.6244   57.0000 
+2598.7250    8.5000    8.9153   86.9870    4.2686    2.5976    0.2256   81.9510    4.4705   57.0000 
+2598.8250    8.5000    8.9562   85.8807    4.4289    2.5934    0.2196   81.0429    4.1876   57.0000 
+2598.9250    8.5000    8.9481   85.4811    4.7045    2.5873    0.2169   80.0827    3.9761   57.0000 
+2599.0250    8.5000    8.9481   87.7283    5.0243    2.5845    0.2169   79.2847    3.9212   57.0000 
+2599.1250    8.5000    8.9072   91.7540    5.2821    2.5859    0.2165   78.9520    3.9363   57.0000 
+2599.2250    8.5000    8.8990   95.4264    5.4161    2.5891    0.2160   79.1490    3.9834   57.0000 
+2599.3250    8.5000    8.9072   98.8836    5.4384    2.5916    0.2161   79.8449    4.0349   57.0000 
+2599.4250    8.5000    8.8908  102.5712    5.3880    2.5906    0.2185   80.7133    4.0971   57.0000 
+2599.5250    8.5000    8.9153  104.0463    5.2886    2.5877    0.2212   81.6087    4.1262   57.0000 
+2599.6250    8.5000    8.9153  106.1975    5.1592    2.5862    0.2234   82.4740    4.1686   57.0000 
+2599.7250    8.5000    8.9317  107.9261    5.0324    2.5865    0.2241   83.1740    4.1998   57.0000 
+2599.8250    8.5000    8.9562  107.1002    4.9396    2.5871    0.2257   83.7607    4.2648   57.0000 
+2599.9250    8.5000    8.9562  105.9478    4.8805    2.5849    0.2286   84.1429    4.3172   57.0000 
+2600.0250    8.5000    8.9562  103.2281    4.8107    2.5841    0.2333   84.4214    4.4590   57.0000 
+2600.1250    8.5000    8.9808  100.8081    4.6812    2.5856    0.2392   84.7663    4.6852   57.0000 
+2600.2250    8.5000    9.0053  100.0897    4.4986    2.5903    0.2424   85.3684    4.8864   57.0000 
+2600.3250    8.5000    8.9890  100.7197    4.3321    2.5941    0.2464   86.3745    5.0956   57.0000 
+2600.4250    8.5000    8.9726  102.2409    4.2527    2.5939    0.2489   87.6663    5.1751   57.0000 
+2600.5250    8.5000    8.9644  103.2012    4.2920    2.5916    0.2547   88.8944    5.3221   57.0000 
+2600.6250    8.5000    8.9562  103.0937    4.4321    2.5865    0.2588   89.7454    5.3587   57.0000 
+2600.7250    8.5000    8.9644  101.4957    4.6097    2.5820    0.2618   90.0811    5.3658   57.0000 
+2600.8250    8.5000    8.9726   99.1140    4.7344    2.5761    0.2605   90.0372    5.2044   57.0000 
+2600.9250    8.5000    8.9644   97.1012    4.7471    2.5730    0.2576   89.7276    5.0476   57.0000 
+2601.0250    8.5000    8.9399   95.4725    4.6715    2.5713    0.2534   89.0551    4.8712   57.0000 
+2601.1250    8.5000    8.9235   94.5582    4.5892    2.5747    0.2504   87.7520    4.8407   57.0000 
+2601.2250    8.5000    8.9153   93.1446    4.5734    2.5789    0.2442   85.9903    4.7189   57.0000 
+2601.3250    8.5000    8.9153   91.6695    4.6526    2.5846    0.2381   84.0204    4.6281   57.0000 
+2601.4250    8.5000    8.9562   91.1318    4.8139    2.5850    0.2326   82.4148    4.4516   57.0000 
+2601.5250    8.5000    8.9644   90.9166    5.0152    2.5823    0.2334   81.4954    4.4240   57.0000 
+2601.6250    8.5000    8.9808   92.3840    5.2055    2.5753    0.2375   81.3337    4.4247   57.0000 
+2601.7250    8.5000    8.9399   94.2586    5.3302    2.5694    0.2412   82.1929    4.4274   57.0000 
+2601.8250    8.5000    8.9235   96.4328    5.3311    2.5646    0.2422   83.7689    4.3642   57.0000 
+2601.9250    8.5000    8.9153   99.0603    5.1817    2.5679    0.2424   85.6806    4.4360   57.0000 
+2602.0250    8.5000    8.9235  101.1807    4.9244    2.5798    0.2431   87.2153    4.6981   57.0000 
+2602.1250    8.5000    8.9481  102.7479    4.6373    2.5919    0.2422   88.0097    4.9117   57.0000 
+2602.2250    8.5000    8.9399  102.0911    4.3821    2.5938    0.2370   88.0561    4.7775   57.0000 
+2602.3250    8.5000    8.9235  101.0923    4.1939    2.5835    0.2283   87.4138    4.2802   57.0000 
+2602.4250    8.5000    8.9072  100.0552    4.0896    2.5787    0.2192   86.2980    3.8788   57.0000 
+2602.5250    8.5000    8.9153   99.4098    4.0744    2.5819    0.2121   84.9571    3.7078   57.0000 
+2602.6250    8.5000    8.9317   99.0795    4.1430    2.5906    0.2074   83.7515    3.7265   57.0000 
+2602.7250    8.5000    8.9562   98.0269    4.2717    2.5900    0.2042   83.0398    3.6078   57.0000 
+2602.8250    8.5000    8.9317   97.7350    4.4226    2.5871    0.2034   82.8071    3.5216   57.0000 
+2602.9250    8.5000    8.9235   97.1357    4.5544    2.5874    0.2049   83.0224    3.5801   57.0000 
+2603.0250    8.5000    8.9072   97.5852    4.6426    2.5944    0.2088   83.4413    3.8482   57.0000 
+2603.1250    8.5000    8.9153   98.2881    4.6814    2.5998    0.2122   83.7418    4.0716   57.0000 
+2603.2250    8.5000    8.9153   96.7516    4.6775    2.5962    0.2149   83.8388    4.0863   57.0000 
+2603.3250    8.5000    8.9072   95.9834    4.6398    2.5897    0.2168   83.5791    4.0216   57.0000 
+2603.4250    8.5000    8.8744   95.7682    4.5871    2.5861    0.2192   83.2306    4.0281   57.0000 
+2603.5250    8.5000    8.9072   95.2228    4.5459    2.5936    0.2220   82.8306    4.2706   57.0000 
+2603.6250    8.5000    8.9399   96.5288    4.5383    2.6039    0.2241   82.4985    4.5488   57.0000 
+2603.7250    8.5000    8.9808   97.0512    4.5760    2.6137    0.2256   82.2872    4.7926   57.0000 
+2603.8250    8.5000    8.9644   96.1447    4.6690    2.6130    0.2279   82.1245    4.8574   57.0000 
+2603.9250    8.5000    8.9562   96.9475    4.8278    2.6149    0.2330   82.9587    5.0634   57.0000 
+2604.0250    8.5000    8.8908   98.9988    5.0273    2.6195    0.2391   85.7980    5.3581   57.0000 
+2604.1250    8.5000    8.8499  101.3497    5.1743    2.6284    0.2433   89.2342    5.6798   57.0000 
+2604.2250    8.5000    8.8499  104.5764    5.1444    2.6257    0.2437   92.4668    5.6375   57.0000 
+2604.3250    8.5000    8.8581  105.0835    4.9161    2.6138    0.2415   92.4327    5.3245   57.0000 
+2604.4250    8.5000    8.8744  102.6711    4.6039    2.5995    0.2390   89.6444    4.9555   57.0000 
+2604.5250    8.5000    8.8663   99.9822    4.3397    2.5949    0.2357   86.3536    4.7566   57.0000 
+2604.6250    8.5000    8.8417   97.6620    4.1864    2.5971    0.2326   83.4281    4.6953   57.0000 
+2604.7250    8.5000    8.8090   96.3483    4.1573    2.6064    0.2280   81.8918    4.7281   57.0000 
+2604.8250    8.5000    8.7926   96.5250    4.2479    2.6130    0.2241   80.6546    4.7296   57.0000 
+2604.9250    8.5000    8.7926   96.4021    4.4374    2.6198    0.2208   79.4128    4.7569   57.0000 
+2605.0250    8.5000    8.7926   94.6504    4.6775    2.6147    0.2194   78.4939    4.6087   57.0000 
+2605.1250    8.5000    8.8090   94.4660    4.9015    2.6050    0.2197   78.2439    4.4226   57.0000 
+2605.2250    8.5000    8.8172   93.3597    5.0568    2.5919    0.2199   78.5944    4.1671   57.0000 
+2605.3250    8.5000    8.8090   92.7874    5.1305    2.5852    0.2200   79.3321    4.0378   57.0000 
+2605.4250    8.5000    8.8417   95.3687    5.1350    2.5837    0.2187   80.2357    3.9624   57.0000 
+2605.5250    8.5000    8.8744   97.3970    5.0829    2.5864    0.2176   81.1510    3.9813   57.0000 
+2605.6250    8.5000    8.8990  100.8849    4.9891    2.5911    0.2178   82.2388    4.0821   57.0000 
+2605.7250    8.5000    8.9153  104.1808    4.8779    2.5907    0.2209   83.3602    4.1778   57.0000 
+2605.8250    8.5000    8.8908  103.4355    4.7734    2.5824    0.2256   84.3158    4.1694   57.0000 
+2605.9250    8.5000    8.8663  101.6839    4.6904    2.5721    0.2289   84.7658    4.0730   57.0000 
+2606.0250    8.5000    8.8826   99.3407    4.6409    2.5667    0.2317   84.6235    4.0586   57.0000 
+2606.1250    8.5000    8.8663   97.4239    4.6364    2.5687    0.2327   84.0510    4.1305   57.0000 
+2606.2250    8.5000    8.8826   97.3624    4.6854    2.5734    0.2315   83.2449    4.1862   57.0000 
+2606.3250    8.5000    8.8990   96.6709    4.7843    2.5783    0.2243   82.2745    4.0432   57.0000 
+2606.4250    8.5000    8.8990   94.7964    4.9191    2.5829    0.2160   81.0112    3.8571   57.0000 
+2606.5250    8.5000    8.9072   91.9077    5.0730    2.5833    0.2077   79.3577    3.5891   57.0000 
+2606.6250    8.5000    8.9399   89.3801    5.2443    2.5905    0.2022   77.5908    3.5488   57.0000 
+2606.7250    8.5000    8.9235   87.5670    5.4451    2.6003    0.1947   76.0556    3.4949   57.0000 
+2606.8250    8.5000    8.8908   87.1752    5.6766    2.6177    0.1884   75.0781    3.6356   57.0000 
+2606.9250    8.5000    8.8663   87.7206    5.8931    2.6250    0.1852   74.6903    3.6728   57.0000 
+2607.0250    8.5000    8.8663   87.7667    6.0119    2.6236    0.1854   74.5612    3.6520   57.0000 
+2607.1250    8.5000    8.8908   89.2879    5.9855    2.6142    0.1879   74.6679    3.5473   57.0000 
+2607.2250    8.5000    8.9153   90.5940    5.8514    2.6025    0.1902   75.1026    3.3884   57.0000 
+2607.3250    8.5000    8.9153   92.1151    5.6885    2.5982    0.1947   76.0434    3.4532   57.0000 
+2607.4250    8.5000    8.8826   94.0512    5.5296    2.5965    0.2017   77.5148    3.6552   57.0000 
+2607.5250    8.5000    8.8744   95.8489    5.3351    2.5983    0.2116   79.0740    4.0194   57.0000 
+2607.6250    8.5000    8.8826   98.1998    5.0505    2.5941    0.2226   80.5679    4.3014   57.0000 
+2607.7250    8.5000    8.9072  101.1039    4.6988    2.5944    0.2312   81.8439    4.5949   57.0000 
+2607.8250    8.5000    8.9153  105.2448    4.3762    2.6037    0.2350   82.9025    4.9067   57.0000 
+2607.9250    8.5000    8.9072  108.1719    4.1445    2.6194    0.2358   83.7730    5.2475   57.0000 
+2608.0250    8.5000    8.9399  110.3845    3.9872    2.6259    0.2366   84.6087    5.4039   57.0000 
+2608.1250    8.5000    8.9644  111.0606    3.8487    2.6227    0.2411   85.5827    5.4903   57.0000 
+2608.2250    8.5000    8.9808  110.2155    3.6970    2.6152    0.2473   86.8434    5.5482   57.0000 
+2608.3250    8.5000    8.9644  110.3999    3.5402    2.6086    0.2548   88.3505    5.6653   57.0000 
+2608.4250    8.5000    8.9562  110.6764    3.4094    2.6051    0.2600   89.8362    5.7664   57.0000 
+2608.5250    8.5000    8.9399  111.1528    3.3205    2.6078    0.2619   91.2316    5.8846   57.0000 
+2608.6250    8.5000    8.9481  112.3129    3.2669    2.6159    0.2609   92.2245    6.0169   57.0000 
+2608.7250    8.5000    8.9562  112.4896    3.2338    2.6165    0.2601   92.7444    5.9991   57.0000 
+2608.8250    8.5000    8.9235  111.9979    3.2151    2.6131    0.2611   92.7423    5.9664   57.0000 
+2608.9250    8.5000    8.9317  111.7827    3.2187    2.6117    0.2610   92.3500    5.9327   57.0000 
+2609.0250    8.5000    8.9399  110.0618    3.2599    2.6191    0.2601   91.8571    6.0516   57.0000 
+2609.1250    8.5000    8.9726  107.3883    3.3488    2.6169    0.2583   91.2592    5.9484   57.0000 
+2609.2250    8.5000    8.9726  105.8978    3.4815    2.6070    0.2576   90.5393    5.7255   57.0000 
+2609.3250    8.5000    8.9726  105.0835    3.6328    2.5943    0.2569   89.8903    5.4516   57.0000 
+2609.4250    8.5000    8.9808  104.4842    3.7481    2.5932    0.2565   89.3735    5.4139   57.0000 
+2609.5250    8.5000    8.9562  105.9132    3.7674    2.5947    0.2552   89.2888    5.4019   57.0000 
+2609.6250    8.5000    8.9399  105.8978    3.6769    2.5969    0.2548   89.5592    5.4306   57.0000 
+2609.7250    8.5000    8.9399  105.8671    3.5265    2.5936    0.2535   89.9893    5.3224   57.0000 
+2609.8250    8.5000    8.9481  107.4651    3.3837    2.5939    0.2560   90.4138    5.4102   57.0000 
+2609.9250    8.5000    8.9726  108.5099    3.2942    2.5973    0.2591   90.5954    5.5819   57.0000 
+2610.0250    8.5000    9.0135  111.4908    3.2759    2.6049    0.2634   90.5250    5.8780   57.0000 
+2610.1250    8.5000    9.0299  113.3807    3.3287    2.6098    0.2622   90.2214    5.9382   57.0000 
+2610.2250    8.5000    9.0380  114.7483    3.4417    2.6093    0.2585   89.8730    5.8030   57.0000 
+2610.3250    8.5000    9.0217  115.3552    3.5884    2.6082    0.2528   89.5633    5.5894   57.0000 
+2610.4250    8.5000    9.0217  114.2796    3.7187    2.6088    0.2519   89.5066    5.5712   57.0000 
+2610.5250    8.5000    9.0217  114.1183    3.7762    2.6129    0.2552   89.6301    5.7651   57.0000 
+2610.6250    8.5000    9.0217  113.2885    3.7362    2.6151    0.2617   89.8775    6.0246   57.0000 
+2610.7250    8.5000    9.0135  113.6727    3.6258    2.6138    0.2684   90.2061    6.2237   57.0000 
+2610.8250    8.5000    9.0135  114.7022    3.5001    2.6091    0.2719   90.4240    6.2447   57.0000 
+2610.9250    8.5000    8.9971  114.6407    3.4053    2.6060    0.2738   90.5158    6.2471   57.0000 
+2611.0250    8.5000    8.9890  114.0722    3.3585    2.6035    0.2713   90.7770    6.1124   57.0000 
+2611.1250    8.5000    8.9971  111.9134    3.3451    2.6001    0.2693   92.9648    5.9789   57.0000 
+2611.2250    8.5000    8.9890  108.7558    3.3386    2.5899    0.2670   96.9577    5.6976   57.0000 
+2611.3250    8.5000    8.9808  106.3972    3.3246    2.5817    0.2661  101.2071    5.5032   57.0000 
+2611.4250    8.5000    8.9890  106.5048    3.3069    2.5817    0.2636  102.7878    5.4210   57.0000 
+2611.5250    8.5000    8.9890  108.3640    3.2967    2.5928    0.2605   99.9423    5.5380   57.0000 
+2611.6250    8.5000    8.9890  110.7149    3.3020    2.6061    0.2591   95.3490    5.7586   57.0000 
+2611.7250    8.5000    9.0053  112.0516    3.3282    2.6142    0.2580   91.1903    5.8839   57.0000 
+2611.8250    8.5000    9.0053  109.8390    3.3777    2.6155    0.2551   89.0862    5.8133   57.0000 
+2611.9250    8.5000    8.9971  105.1219    3.4469    2.6062    0.2518   88.7918    5.5167   57.0000 
+2612.0250    8.5000    9.0380  102.1641    3.5247    2.5950    0.2509   88.6755    5.2634   57.0000 
+2612.1250    8.5000    9.0462  100.3970    3.6003    2.5871    0.2558   88.5801    5.2677   57.0000 
+2612.2250    8.5000    9.0626  101.5648    3.6708    2.5904    0.2612   88.6546    5.5126   57.0000 
+2612.3250    8.5000    9.0626  104.9759    3.7356    2.5948    0.2659   88.7265    5.7605   57.0000 
+2612.4250    8.5000    9.0299  106.1437    3.7904    2.5969    0.2696   88.6827    5.9247   57.0000 
+2612.5250    8.5000    9.0299  106.7276    3.8339    2.5945    0.2739   88.4918    6.0191   57.0000 
+2612.6250    8.5000    9.0135  105.8056    3.8725    2.5917    0.2753   88.1066    6.0123   57.0000 
+2612.7250    8.5000    9.0217  104.8223    3.9122    2.5905    0.2711   87.7832    5.8476   57.0000 
+2612.8250    8.5000    9.0299  104.5687    3.9529    2.5869    0.2635   87.3898    5.5211   57.0000 
+2612.9250    8.5000    8.9726  104.6148    3.9879    2.5814    0.2605   86.8031    5.3116   57.0000 
+2613.0250    8.5000    9.0053  105.1833    4.0171    2.5698    0.2645   86.0694    5.2140   57.0000 
+2613.1250    8.5000    8.9890  104.3536    4.0501    2.5628    0.2707   85.2423    5.2782   57.0000 
+2613.2250    8.5000    8.9890  103.4471    4.1016    2.5586    0.2729   84.6265    5.2697   57.0000 
+2613.3250    8.5000    9.0135  102.7095    4.1751    2.5635    0.2695   84.3306    5.2534   57.0000 
+2613.4250    8.5000    9.0217  101.0040    4.2577    2.5689    0.2649   84.2342    5.2081   57.0000 
+2613.5250    8.5000    9.0380   99.5174    4.3300    2.5771    0.2611   84.1842    5.2434   57.0000 
+2613.6250    8.5000    9.0299   98.4572    4.3724    2.5812    0.2607   84.1020    5.3151   57.0000 
+2613.7250    8.5000    9.0544   97.2203    4.3606    2.5835    0.2600   83.9755    5.3356   57.0000 
+2613.8250    8.5000    9.0544   96.9783    4.2818    2.5801    0.2584   84.0469    5.2169   57.0000 
+2613.9250    8.5000    9.0380   97.5314    4.1548    2.5743    0.2508   84.4179    4.8454   57.0000 
+2614.0250    8.5000    9.0462   98.2459    4.0229    2.5698    0.2432   85.0934    4.5023   57.0000 
+2614.1250    8.5000    9.0544   99.1179    3.9260    2.5686    0.2381   87.5388    4.3081   57.0000 
+2614.2250    8.5000    9.0708  100.8311    3.8847    2.5733    0.2409   91.8918    4.4965   57.0000 
+2614.3250    8.5000    9.0708  102.6634    3.9038    2.5737    0.2446   96.7903    4.6280   57.0000 
+2614.4250    8.5000    9.0626  103.1743    3.9767    2.5743    0.2467   99.8985    4.7109   57.0000 
+2614.5250    8.5000    9.0462  102.9746    4.0845    2.5762    0.2448   98.7444    4.6826   57.0000 
+2614.6250    8.5000    9.0299  101.1039    4.1899    2.5855    0.2448   94.1577    4.8690   57.0000 
+2614.7250    8.5000    9.0299   99.6365    4.2523    2.5962    0.2452   89.6362    5.0957   57.0000 
+2614.8250    8.5000    9.0217   99.7440    4.2601    2.6004    0.2449   86.8444    5.1716   57.0000 
+2614.9250    8.5000    9.0135  100.4009    4.2389    2.5984    0.2410   86.1903    5.0002   57.0000 
+2615.0250    8.5000    9.0217  102.9823    4.2254    2.5927    0.2373   86.2730    4.7647   57.0000 
+2615.1250    8.5000    9.0053  102.7979    4.2463    2.5882    0.2366   86.2082    4.6508   57.0000 
+2615.2250    8.5000    8.9971  101.7031    4.3007    2.5849    0.2368   86.1270    4.5910   57.0000 
+2615.3250    8.5000    9.0135  100.8580    4.3603    2.5874    0.2364   86.0709    4.6291   57.0000 
+2615.4250    8.5000    9.0299   98.1230    4.3846    2.5925    0.2336   86.0607    4.6363   57.0000 
+2615.5250    8.5000    9.0544   98.5455    4.3512    2.6047    0.2332   86.0964    4.8696   57.0000 
+2615.6250    8.5000    9.0462   99.1909    4.2726    2.6093    0.2341   86.1097    4.9892   57.0000 
+2615.7250    8.5000    9.0380   99.3292    4.1883    2.6074    0.2362   86.6286    5.0205   57.0000 
+2615.8250    8.5000    9.0053  100.1973    4.1444    2.5942    0.2355   87.5102    4.7339   57.0000 
+2615.9250    8.5000    8.9971   99.6134    4.1725    2.5851    0.2331   88.5235    4.4705   57.0000 
+2616.0250    8.5000    9.0135   99.4982    4.2733    2.5820    0.2305   90.9469    4.3239   57.0000 
+2616.1250    8.5000    9.0299  100.4892    4.4041    2.5888    0.2304   92.4276    4.4550   57.0000 
+2616.2250    8.5000    9.0299  101.9182    4.4812    2.5975    0.2324   93.8383    4.6968   57.0000 
+2616.3250    8.5000    9.0299  103.4778    4.4421    2.6050    0.2343   93.7617    4.9110   57.0000 
+2616.4250    8.5000    9.0053  104.7838    4.3119    2.6050    0.2362   91.1133    4.9746   57.0000 
+2616.5250    8.5000    9.0135  104.4304    4.1677    2.5965    0.2367   88.7199    4.8217   57.0000 
+2616.6250    8.5000    9.0053  102.5213    4.0631    2.5899    0.2391   86.5189    4.7686   57.0000 
+2616.7250    8.5000    8.9808  102.8555    4.0095    2.5864    0.2419   85.9408    4.7906   57.0000 
+2616.8250    8.5000    9.0135  103.0975    3.9936    2.5938    0.2455   86.1265    5.0579   57.0000 
+2616.9250    8.5000    8.9971  104.1039    3.9955    2.5970    0.2483   86.2985    5.2151   57.0000 
+2617.0250    8.5000    9.0299  107.2922    3.9932    2.5988    0.2497   86.4582    5.3016   57.0000 
+2617.1250    8.5000    9.0544  107.1002    3.9665    2.5934    0.2507   86.5204    5.2252   57.0000 
+2617.2250    8.5000    9.0708  105.6020    3.9097    2.5922    0.2495   86.5036    5.1609   57.0000 
+2617.3250    8.5000    9.0789  103.2972    3.8389    2.5925    0.2471   86.5240    5.0870   57.0000 
+2617.4250    8.5000    9.0544   99.4943    3.7795    2.5985    0.2435   86.6388    5.0883   57.0000 
+2617.5250    8.5000    9.0217   97.7081    3.7450    2.6040    0.2410   86.7990    5.1146   57.0000 
+2617.6250    8.5000    8.9726   97.9117    3.7328    2.6095    0.2427   86.9408    5.2794   57.0000 
+2617.7250    8.5000    8.9808   99.5558    3.7337    2.6053    0.2470   87.0352    5.3392   57.0000 
+2617.8250    8.5000    8.9890  100.2703    3.7436    2.5944    0.2528   87.0980    5.3152   57.0000 
+2617.9250    8.5000    9.0053   98.7798    3.7683    2.5828    0.2520   87.0964    5.0541   57.0000 
+2618.0250    8.5000    9.0299   96.1370    3.8234    2.5835    0.2480   86.8500    4.9386   57.0000 
+2618.1250    8.5000    9.0217   92.1728    3.9293    2.5902    0.2402   86.2684    4.8113   57.0000 
+2618.2250    8.5000    9.0135   89.6106    4.1045    2.5969    0.2324   85.4806    4.6854   57.0000 
+2618.3250    8.5000    9.0544   88.7501    4.3457    2.5929    0.2231   84.8929    4.2930   57.0000 
+2618.4250    8.5000    9.0626   87.9012    4.5974    2.5930    0.2158   84.6735    4.0548   57.0000 
+2618.5250    8.5000    9.0789   87.9281    4.7514    2.5896    0.2137   84.8031    3.9168   57.0000 
+2618.6250    8.5000    9.1117   88.4659    4.7265    2.5919    0.2163   85.1439    4.0484   57.0000 
+2618.7250    8.5000    9.1117   89.7258    4.5595    2.5856    0.2182   85.5393    3.9841   57.0000 
+2618.8250    8.5000    9.1117   93.0063    4.3607    2.5873    0.2164   85.9526    3.9606   57.0000 
+2618.9250    8.5000    9.1280   96.3060    4.2117    2.5850    0.2114   86.2633    3.7469   57.0000 
+2619.0250    8.5000    9.1444   99.6403    4.1342    2.5841    0.2083   86.2260    3.6254   57.0000 
+2619.1250    8.5000    9.1444  101.4304    4.1161    2.5756    0.2081   85.7347    3.4463   57.0000 
+2619.2250    8.5000    9.1198  100.8580    4.1354    2.5719    0.2112   84.9168    3.4759   57.0000 
+2619.3250    8.5000    9.1525  100.0936    4.1724    2.5687    0.2137   84.0291    3.4994   57.0000 
+2619.4250    8.5000    9.1362   97.8041    4.2109    2.5731    0.2163   83.3475    3.6724   57.0000 
+2619.5250    8.5000    9.1934   95.7452    4.2501    2.5769    0.2169   82.8321    3.7670   57.0000 
+2619.6250    8.5000    9.1934   94.0857    4.3070    2.5843    0.2176   82.4888    3.9398   57.0000 
+2619.7250    8.5000    9.2016   93.2061    4.4028    2.5867    0.2173   82.1719    3.9774   57.0000 
+2619.8250    8.5000    9.2180   94.3277    4.5351    2.5937    0.2174   82.0010    4.1202   57.0000 
+2619.9250    8.5000    9.2671   96.6556    4.6645    2.6070    0.2161   81.9173    4.3438   57.0000 
+2620.0250    8.5000    9.3080  100.0513    4.7429    2.6214    0.2140   82.0066    4.5618   57.0000 
+2620.1250    8.5000    9.3734  102.5251    4.7584    2.6292    0.2105   82.2077    4.6006   57.0000 
+2620.2250    8.5000    9.3979  103.6468    4.7371    2.6306    0.2078   82.4607    4.5379   57.0000 
+2620.3250    8.5000    9.3734  104.3805    4.7129    2.6335    0.2055   82.9735    4.5219   57.0000 
+2620.4250    8.5000    9.3570  104.7954    4.7149    2.6343    0.2051   83.6515    4.5219   57.0000 
+2620.5250    8.5000    9.3407  105.1564    4.7733    2.6264    0.2048   84.4107    4.3559   57.0000 
+2620.6250    8.5000    9.3325  105.1411    4.9174    2.6119    0.2049   84.9281    4.0688   57.0000 
+2620.7250    8.5000    9.3407  104.4266    5.1560    2.5936    0.2048   84.9582    3.6977   57.0000 
+2620.8250    8.5000    9.3489  102.4522    5.4632    2.5793    0.2047   84.3204    3.4103   57.0000 
+2620.9250    8.5000    9.3489  100.6390    5.7750    2.5679    0.2063   83.1051    3.2337   57.0000 
+2621.0250    8.5000    9.3407   99.6249    6.0293    2.5668    0.2083   81.5291    3.2792   57.0000 
+2621.1250    8.5000    9.3570   99.4060    6.2251    2.5705    0.2104   79.8786    3.4220   57.0000 
+2621.2250    8.5000    9.3161  100.0820    6.4264    2.5830    0.2120   78.5908    3.7265   57.0000 
+2621.3250    8.5000    9.3161  100.9271    6.6649    2.5892    0.2133   77.7959    3.8956   57.0000 
+2621.4250    8.5000    9.2834  101.6339    6.8716    2.5892    0.2135   77.5694    3.9017   57.0000 
+2621.5250    8.5000    9.2425  100.8503    6.9335    2.5786    0.2121   77.8362    3.6403   57.0000 
+2621.6250    8.5000    9.2425  101.1192    6.8317    2.5714    0.2123   78.4087    3.5056   57.0000 
+2621.7250    8.5000    9.2016  100.1973    6.6523    2.5784    0.2170   79.2061    3.8010   57.0000 
+2621.8250    8.5000    9.2180   99.5904    6.4835    2.5945    0.2218   80.0663    4.2829   57.0000 
+2621.9250    8.5000    9.1853  101.5802    6.3661    2.6122    0.2232   80.7525    4.6838   57.0000 
+2622.0250    8.5000    9.1853  102.7633    6.2999    2.6124    0.2193   81.2622    4.5580   57.0000 
+2622.1250    8.5000    9.1607  105.8978    6.2611    2.6027    0.2166   81.4847    4.2759   57.0000 
+2622.2250    8.5000    9.1198  108.2948    6.2191    2.5895    0.2167   81.5082    4.0134   57.0000 
+2622.3250    8.5000    9.1198  107.5419    6.1547    2.5864    0.2201   81.3668    4.0660   57.0000 
+2622.4250    8.5000    9.1035  105.9785    6.0609    2.5868    0.2232   81.1245    4.1768   57.0000 
+2622.5250    8.5000    9.1280  103.8734    5.9422    2.5887    0.2244   80.8337    4.2552   57.0000 
+2622.6250    8.5000    9.1444  102.3600    5.8159    2.5891    0.2251   80.7102    4.2857   57.0000 
+2622.7250    8.5000    9.1362  102.5674    5.7068    2.5901    0.2250   80.8061    4.3003   57.0000 
+2622.8250    8.5000    9.1362  102.4983    5.6301    2.5868    0.2255   81.2505    4.2504   57.0000 
+2622.9250    8.5000    9.1444  101.6839    5.5765    2.5750    0.2237   81.9378    3.9557   57.0000 
+2623.0250    8.5000    9.1362  101.0462    5.5170    2.5663    0.2215   82.7010    3.7083   57.0000 
+2623.1250    8.5000    9.1525  100.1704    5.4271    2.5656    0.2181   83.3245    3.5815   57.0000 
+2623.2250    8.5000    9.1280   99.7440    5.3073    2.5746    0.2148   83.5985    3.6534   57.0000 
+2623.3250    8.5000    9.1117   99.5596    5.1792    2.5823    0.2121   83.4490    3.7163   57.0000 
+2623.4250    8.5000    9.0544   98.2997    5.0747    2.5882    0.2090   82.8362    3.7302   57.0000 
+2623.5250    8.5000    9.0462   95.7029    5.0252    2.5952    0.2050   81.9214    3.7388   57.0000 
+2623.6250    8.5000    9.0299   92.9525    5.0420    2.6020    0.2009   80.8071    3.7369   57.0000 
+2623.7250    8.5000    9.0299   91.2470    5.1085    2.6019    0.1982   79.7342    3.6466   57.0000 
+2623.8250    8.5000    9.0217   90.8244    5.1907    2.5949    0.1992   78.9036    3.5366   57.0000 
+2623.9250    8.5000    9.0053   93.2522    5.2672    2.5819    0.1999   78.3602    3.3017   57.0000 
+2624.0250    8.5000    8.9562   97.3163    5.3472    2.5729    0.2018   78.1265    3.1861   57.0000 
+2624.1250    8.5000    8.9235   99.6902    5.4592    2.5715    0.2032   78.1633    3.2028   57.0000 
+2624.2250    8.5000    8.8908  101.1884    5.6173    2.5794    0.2062   78.5765    3.4612   57.0000 
+2624.3250    8.5000    8.8417  100.8004    5.8033    2.5873    0.2085   79.3622    3.6962   57.0000 
+2624.4250    8.5000    8.8335   99.0026    5.9671    2.5870    0.2113   80.4439    3.7829   57.0000 
+2624.5250    8.5000    8.8581   98.6339    6.0543    2.5822    0.2138   81.5153    3.7713   57.0000 
+2624.6250    8.5000    8.8826   99.0180    6.0410    2.5779    0.2159   82.6990    3.7525   57.0000 
+2624.7250    8.5000    8.8744  100.9310    5.9553    2.5793    0.2159   85.3571    3.7841   57.0000 
+2624.8250    8.5000    8.8499  103.7813    5.8521    2.5778    0.2158   89.3148    3.7487   57.0000 
+2624.9250    8.5000    8.8090  105.2794    5.7822    2.5753    0.2154   93.2475    3.6861   57.0000 
+2625.0250    8.5000    8.8090  106.3780    5.7736    2.5731    0.2155   94.5490    3.6458   57.0000 
+2625.1250    8.5000    8.8254  107.3883    5.8264    2.5767    0.2143   91.7765    3.6769   57.0000 
+2625.2250    8.5000    8.8254  107.9414    5.9107    2.5820    0.2142   87.3480    3.7816   57.0000 
+2625.3250    8.5000    8.8254  109.7084    5.9666    2.5825    0.2150   83.2439    3.8170   57.0000 
+2625.4250    8.5000    8.8172  110.6764    5.9667    2.5790    0.2159   81.1092    3.7782   57.0000 
+2625.5250    8.5000    8.7926  108.3255    5.9533    2.5723    0.2156   80.6709    3.6313   57.0000 
+2625.6250    8.5000    8.7926  105.1449    5.9889    2.5634    0.2133   80.5291    3.3755   57.0000 
+2625.7250    8.5000    8.8090  100.5968    6.0854    2.5547    0.2127   80.3684    3.1837   57.0000 
+2625.8250    8.5000    8.8090   97.1703    6.2050    2.5515    0.2116   80.2000    3.0810   57.0000 
+2625.9250    8.5000    8.8335   97.2318    6.2804    2.5602    0.2120   80.0704    3.2715   57.0000 
+2626.0250    8.5000    8.8335   97.6927    6.2384    2.5753    0.2104   80.0327    3.5208   57.0000 
+2626.1250    8.5000    8.8417   99.9361    6.0605    2.5894    0.2100   80.2204    3.7886   57.0000 
+2626.2250    8.5000    8.8826  101.8567    5.8095    2.5941    0.2091   80.7117    3.8523   57.0000 
+2626.3250    8.5000    8.8663  101.2729    5.5728    2.5925    0.2085   82.2066    3.8012   57.0000 
+2626.4250    8.5000    8.8663  100.2741    5.3882    2.5858    0.2096   84.0867    3.7031   57.0000 
+2626.5250    8.5000    8.8417   97.5698    5.2434    2.5871    0.2106   85.7775    3.7624   57.0000 
+2626.6250    8.5000    8.8172   94.3892    5.1090    2.5923    0.2136   86.4306    3.9667   57.0000 
+2626.7250    8.5000    8.8581   92.5646    4.9704    2.6050    0.2135   85.3704    4.2172   57.0000 
+2626.8250    8.5000    8.8744   91.9039    4.8345    2.6091    0.2142   84.2439    4.3204   57.0000 
+2626.9250    8.5000    8.8826   92.2265    4.7170    2.6103    0.2145   83.4046    4.3558   57.0000 
+2627.0250    8.5000    8.8744   93.0947    4.6142    2.6034    0.2176   83.5464    4.3231   57.0000 
+2627.1250    8.5000    8.8499   94.3162    4.5090    2.5976    0.2217   84.1010    4.3410   57.0000 
+2627.2250    8.5000    8.8417   94.3469    4.3903    2.5870    0.2245   84.6607    4.2232   57.0000 
+2627.3250    8.5000    8.8254   94.3623    4.2638    2.5821    0.2255   85.1179    4.1601   57.0000 
+2627.4250    8.5000    8.7926   94.5774    4.1402    2.5806    0.2266   85.3852    4.1633   57.0000 
+2627.5250    8.5000    8.7599   95.0883    4.0328    2.5860    0.2280   85.3546    4.3187   57.0000 
+2627.6250    8.5000    8.7681   97.0090    3.9517    2.5901    0.2310   85.0964    4.5025   57.0000 
+2627.7250    8.5000    8.8090   98.0385    3.9001    2.5912    0.2321   84.7974    4.5625   57.0000 
+2627.8250    8.5000    8.8090   98.1383    3.8716    2.5850    0.2349   84.6566    4.5293   57.0000 
+2627.9250    8.5000    8.8417   97.3547    3.8539    2.5758    0.2360   84.5776    4.3835   57.0000 
+2628.0250    8.5000    8.8417   95.5416    3.8378    2.5687    0.2359   84.4867    4.2387   57.0000 
+2628.1250    8.5000    8.8499   95.1190    3.8235    2.5671    0.2324   84.3051    4.0903   57.0000 
+2628.2250    8.5000    8.8581   95.8873    3.8219    2.5717    0.2283   84.1245    4.0437   57.0000 
+2628.3250    8.5000    8.8663   96.2561    3.8411    2.5763    0.2266   84.0658    4.0808   57.0000 
+2628.4250    8.5000    8.8335   98.0231    3.8713    2.5833    0.2252   84.2158    4.1724   57.0000 
+2628.5250    8.5000    8.8008   98.9296    3.8829    2.5869    0.2230   84.6286    4.1728   57.0000 
+2628.6250    8.5000    8.8172   98.8298    3.8466    2.5907    0.2184   85.1163    4.0923   57.0000 
+2628.7250    8.5000    8.8172   99.7671    3.7603    2.5954    0.2120   85.5173    3.9741   57.0000 
+2628.8250    8.5000    8.8581   97.9232    3.6664    2.5993    0.2036   85.4980    3.7732   57.0000 
+2628.9250    8.5000    8.8663   97.3163    3.6286    2.6023    0.1948   84.9908    3.5375   57.0000 
+2629.0250    8.5000    8.8581   98.0654    3.6994    2.6006    0.1903   84.2005    3.3554   57.0000 
+2629.1250    8.5000    8.8254   99.4482    3.8993    2.5971    0.1925   83.2913    3.3595   57.0000 
+2629.2250    8.5000    8.8417  103.8273    4.1923    2.5935    0.2041   82.6122    3.6738   57.0000 
+2629.3250    8.5000    8.8254  106.2243    4.4662    2.5922    0.2191   82.2969    4.1482   57.0000 
+2629.4250    8.5000    8.8744  106.6238    4.5796    2.5963    0.2343   82.5602    4.7343   57.0000 
+2629.5250    8.5000    8.8581  104.6801    4.4711    2.5987    0.2427   83.3923    5.0637   57.0000 
+2629.6250    8.5000    8.8663  101.3766    4.2107    2.5962    0.2478   84.7311    5.1859   57.0000 
+2629.7250    8.5000    8.8663  100.8849    3.9171    2.5867    0.2508   86.1668    5.0947   57.0000 
+2629.8250    8.5000    8.8335  103.2857    3.6667    2.5767    0.2546   87.4260    5.0213   57.0000 
+2629.9250    8.5000    8.8417  108.2641    3.4721    2.5717    0.2565   88.5240    4.9833   57.0000 
+2630.0250    8.5000    8.8417  112.5357    3.3173    2.5753    0.2569   89.4975    5.0693   57.0000 
+2630.1250    8.5000    8.8663  113.8033    3.1873    2.5857    0.2556   90.4867    5.2332   57.0000 
+2630.2250    8.5000    8.8744  111.4831    3.0795    2.5988    0.2531   91.2781    5.4128   57.0000 
+2630.3250    8.5000    8.8663  106.5739    3.0043    2.6059    0.2490   91.4413    5.4188   57.0000 
+2630.4250    8.5000    8.8826  103.1398    2.9789    2.6076    0.2451   90.9066    5.3217   57.0000 
+2630.5250    8.5000    8.8826  100.2357    3.0165    2.6049    0.2439   89.7765    5.2299   57.0000 
+2630.6250    8.5000    8.9153   99.0833    3.1112    2.6061    0.2487   88.4959    5.4126   57.0000 
+2630.7250    8.5000    8.9153   99.4290    3.2299    2.6091    0.2575   87.5179    5.7667   57.0000 
+2630.8250    8.5000    8.9235   99.4751    3.3222    2.6099    0.2658   87.0684    6.0582   57.0000 
+2630.9250    8.5000    8.9153  100.7428    3.3510    2.6071    0.2688   87.2316    6.1019   57.0000 
+2631.0250    8.5000    8.8990  103.8466    3.3102    2.6047    0.2682   87.8357    6.0320   57.0000 
+2631.1250    8.5000    8.8990  107.0886    3.2215    2.6076    0.2669   88.7449    6.0461   57.0000 
+2631.2250    8.5000    8.8581  109.4319    3.1168    2.6124    0.2674   89.7475    6.1630   57.0000 
+2631.3250    8.5000    8.8663  110.9223    3.0197    2.6133    0.2690   90.7852    6.2338   57.0000 
+2631.4250    8.5000    8.8499  108.9017    2.9407    2.6067    0.2723   91.5867    6.2118   57.0000 
+2631.5250    8.5000    8.8499  106.2359    2.8848    2.5937    0.2763   92.0112    6.0848   57.0000 
+2631.6250    8.5000    8.8499  104.3306    2.8551    2.5793    0.2767   91.9510    5.8096   57.0000 
+2631.7250    8.5000    8.8826  102.1641    2.8536    2.5676    0.2714   91.4847    5.3986   57.0000 
+2631.8250    8.5000    8.8663  101.4419    2.8812    2.5620    0.2612   90.9490    4.9484   57.0000 
+2631.9250    8.5000    8.8826  100.6890    2.9372    2.5597    0.2534   90.5561    4.6396   57.0000 
+2632.0250    8.5000    8.8663   98.6915    3.0173    2.5607    0.2485   91.0923    4.4961   57.0000 
+2632.1250    8.5000    8.8417   98.2613    3.1131    2.5611    0.2448   92.1847    4.3825   57.0000 
+2632.2250    8.5000    8.8499   98.7376    3.2204    2.5662    0.2391   92.9969    4.2937   57.0000 
+2632.3250    8.5000    8.8417  101.3574    3.3477    2.5721    0.2348   92.4214    4.2695   57.0000 
+2632.4250    8.5000    8.8990  105.3139    3.5109    2.5820    0.2342   90.0031    4.4464   57.0000 
+2632.5250    8.5000    8.8826  107.5573    3.7083    2.5885    0.2397   87.3949    4.7599   57.0000 
+2632.6250    8.5000    8.8908  109.4472    3.8933    2.5950    0.2466   85.6923    5.1200   57.0000 
+2632.7250    8.5000    8.8990  107.7263    3.9892    2.6000    0.2538   85.5158    5.4616   57.0000 
+2632.8250    8.5000    8.9072  105.9439    3.9694    2.6040    0.2551   86.3878    5.5841   57.0000 
+2632.9250    8.5000    8.9317  104.4842    3.9092    2.6073    0.2529   87.0265    5.5760   57.0000 
+2633.0250    8.5000    8.9235  101.6263    3.9050    2.6040    0.2478   87.1041    5.3383   57.0000 
+2633.1250    8.5000    8.8990   99.5750    3.9760    2.6037    0.2446   86.5837    5.2278   57.0000 
+2633.2250    8.5000    8.9153   95.6492    4.0719    2.6035    0.2402   85.8189    5.0784   57.0000 
+2633.3250    8.5000    8.9072   91.8923    4.1536    2.6058    0.2356   85.1622    4.9700   57.0000 
+2633.4250    8.5000    8.8990   89.7565    4.2397    2.6009    0.2301   84.8250    4.6864   57.0000 
+2633.5250    8.5000    8.9153   89.9102    4.3705    2.5889    0.2286   84.7015    4.3987   57.0000 
+2633.6250    8.5000    8.8744   92.7528    4.5513    2.5794    0.2313   84.6536    4.2975   57.0000 
+2633.7250    8.5000    8.8826   96.4866    4.7278    2.5758    0.2375   84.7684    4.4337   57.0000 
+2633.8250    8.5000    8.8990   99.0526    4.8146    2.5803    0.2426   85.1939    4.6917   57.0000 
+2633.9250    8.5000    8.8499  100.5584    4.7609    2.5839    0.2428   85.9862    4.7733   57.0000 
+2634.0250    8.5000    8.8581  101.0654    4.5913    2.5864    0.2404   86.7587    4.7431   57.0000 
+2634.1250    8.5000    8.8581   99.2370    4.3890    2.5863    0.2363   86.8821    4.6049   57.0000 
+2634.2250    8.5000    8.8417   96.2254    4.2558    2.5856    0.2292   86.0791    4.3534   57.0000 
+2634.3250    8.5000    8.8499   90.4173    4.2857    2.5816    0.2153   84.4352    3.8091   57.0000 
+2634.4250    8.5000    8.8499   83.0496    4.5567    2.5700    0.1962   82.3276    2.9407   57.0000 
+2634.5250    8.5000    8.8499   76.5731    5.1073    2.5512    0.1790   80.2806    1.9904   57.0000 
+2634.6250    8.5000    8.8499   71.7791    5.9047    2.5319    0.1666   78.4092    1.1934   57.0000 
+2634.7250    8.5000    8.8335   68.7368    6.8251    2.5201    0.1597   76.9000    0.7251   57.0000 
+2634.8250    8.5000    8.8335   65.6407    7.7236    2.5117    0.1537   75.8775    0.3574   57.0000 
+2634.9250    8.5000    8.8254   62.2987    8.5067    2.4945    0.1492   75.1061   -0.1386   54.0000 
+2635.0250    8.5000    8.8581   58.9952    9.1942    2.4660    0.1456   74.8469   -0.8252   25.0000 
+2635.1250    8.5000    8.8581   57.2743    9.8454    2.4406    0.1443   75.0184   -1.3791   49.0000 
+2635.2250    8.5000    8.8826   57.7890   10.5192    2.4308    0.1427   75.5582   -1.6263   49.0000 
+2635.3250    8.5000    8.8581   60.3704   11.1798    2.4318    0.1406   76.6714   -1.6787   49.0000 
+2635.4250    8.5000    8.8581   63.8813   11.7424    2.4285    0.1381   77.7265   -1.8262   49.0000 
+2635.5250    8.5000    8.8417   67.4307   12.1568    2.4157    0.1359   78.6429   -2.1547   49.0000 
+2635.6250    8.5000    8.8499   71.6792   12.4704    2.4057    0.1332   78.9122   -2.4448   49.0000 
+2635.7250    8.5000    8.8499   75.8125   12.7659    2.4098    0.1316   78.3102   -2.4193   49.0000 
+2635.8250    8.5000    8.8335   79.4234   13.0164    2.4408    0.1311   77.2092   -1.8136   49.0000 
+2635.9250    8.5000    8.8581   82.0278   13.1160    2.4792    0.1332   76.0776   -0.9758   25.0000 
+2636.0250    8.5000    8.8417   82.4580   12.9809    2.5106    0.1344   75.3602   -0.3106   25.0000 
+2636.1250    8.5000    8.8335   80.8677   12.6860    2.5085    0.1369   75.2245   -0.2674   54.0000 
+2636.2250    8.5000    8.8090   79.1161   12.3650    2.4932    0.1405   75.2765   -0.4517   25.0000 
+2636.3250    8.5000    8.7845   77.7486   12.1102    2.4752    0.1468   75.3429   -0.6033   25.0000 
+2636.4250    8.5000    8.8172   76.0891   11.9359    2.4756    0.1513   75.5439   -0.4463   25.0000 
+2636.5250    8.5000    8.8008   73.9840   11.8164    2.4899    0.1527   75.9643   -0.1129   54.0000 
+2636.6250    8.5000    8.8335   68.8213   11.7198    2.5142    0.1508   76.5796    0.3126   57.0000 
+2636.7250    8.5000    8.8090   61.1617   11.6492    2.5272    0.1464   77.1867    0.4238   57.0000 
+2636.8250    8.5000    8.8090   52.8183   11.6406    2.5135    0.1397   77.6429   -0.0729   54.0000 
+2636.9250    8.5000    8.8581   45.3508   11.7960    2.4713    0.1302   78.1908   -1.2349   49.0000 
+2637.0250    8.5000    8.8335   40.8180   12.2701    2.4233    0.1207   78.9786   -2.5104   49.0000 
+2637.1250    8.5000    8.8744   37.7987   13.2694    2.3901    0.1121   79.9240   -3.4611   49.0000 
+2637.2250    8.5000    8.8908   36.9536   14.9774    2.3790    0.1070   80.5801   -3.8542   49.0000 
+2637.3250    8.5000    8.8908   37.4299   17.4600    2.3855    0.1040   80.7199   -3.8232   49.0000 
+2637.4250    8.5000    8.8744   38.5670   20.4543    2.3998    0.1024   80.4214   -3.5915   49.0000 
+2637.5250    8.5000    8.8417   41.1022   23.4178    2.4176    0.1009   80.0842   -3.2864   49.0000 
+2637.6250    8.5000    8.8581   42.8078   25.6392    2.4331    0.0989   79.9056   -3.0407   49.0000 
+2637.7250    8.5000    8.8744   42.8769   26.6808    2.4450    0.0980   79.9240   -2.8337   49.0000 
+2637.8250    8.5000    8.8744   41.6093   26.6186    2.4504    0.0980   79.9612   -2.7244   49.0000 
+2637.9250    8.5000    8.8663   40.6567   25.7483    2.4519    0.1001   79.9403   -2.6243   49.0000 
+2638.0250    8.5000    8.8499   40.4415   24.4754    2.4520    0.1029   79.8597   -2.5293   49.0000 
+2638.1250    8.5000    8.8090   42.4083   23.0270    2.4505    0.1066   79.7520   -2.4367   49.0000 
+2638.2250    8.5000    8.8008   45.9961   21.4242    2.4495    0.1107   79.6077   -2.3188   49.0000 
+2638.3250    8.5000    8.8172   48.4008   19.5887    2.4489    0.1154   79.4668   -2.1734   49.0000 
+2638.4250    8.5000    8.8008   51.1589   17.7310    2.4560    0.1194   79.3872   -1.8998   49.0000 
+2638.5250    8.5000    8.7845   52.3958   16.2003    2.4619    0.1219   79.4306   -1.6993   49.0000 
+2638.6250    8.5000    8.8254   52.5187   15.1504    2.4664    0.1217   79.4668   -1.6158   49.0000 
+2638.7250    8.5000    8.8417   52.7108   14.5164    2.4670    0.1194   79.2005   -1.6781   49.0000 
+2638.8250    8.5000    8.8744   51.2741   14.1679    2.4715    0.1160   78.7602   -1.7019   49.0000 
+2638.9250    8.5000    8.8826   49.9219   13.9899    2.4774    0.1132   78.1515   -1.6806   49.0000 
+2639.0250    8.5000    8.8581   48.6850   13.9193    2.4754    0.1102   77.8709   -1.8191   49.0000 
+2639.1250    8.5000    8.8663   47.6786   13.9152    2.4620    0.1084   77.9015   -2.1486   49.0000 
+2639.2250    8.5000    8.8744   48.4085   14.0332    2.4474    0.1065   78.1908   -2.5017   49.0000 
+2639.3250    8.5000    8.8663   49.6838   14.3825    2.4388    0.1077   78.4832   -2.6345   49.0000 
+2639.4250    8.5000    8.8663   51.3586   15.0188    2.4396    0.1099   78.4862   -2.5456   49.0000 
+2639.5250    8.5000    8.8663   53.3177   15.8249    2.4387    0.1146   78.2796   -2.4053   49.0000 
+2639.6250    8.5000    8.8908   55.2076   16.4590    2.4391    0.1211   78.1571   -2.1828   49.0000 
+2639.7250    8.5000    8.8908   56.3907   16.5496    2.4388    0.1287   78.1638   -1.9321   49.0000 
+2639.8250    8.5000    8.9072   57.3818   15.9630    2.4412    0.1366   78.3112   -1.6231   49.0000 
+2639.9250    8.5000    8.8744   58.7493   14.9549    2.4479    0.1399   78.5704   -1.3774   49.0000 
+2640.0250    8.5000    8.8499   58.7186   13.8940    2.4610    0.1414   78.6464   -1.0662   49.0000 
+2640.1250    8.5000    8.8663   58.7340   13.0388    2.4817    0.1406   78.7230   -0.6800   25.0000 
+2640.2250    8.5000    8.8908   57.4125   12.4860    2.4981    0.1422   78.8097   -0.2986   54.0000 
+2640.3250    8.5000    8.8826   53.5943   12.2107    2.5012    0.1423   78.8959   -0.2313   54.0000 
+2640.4250    8.5000    8.8908   49.6684   12.1532    2.4894    0.1404   79.0031   -0.5330   25.0000 
+2640.5250    8.5000    8.8663   45.8885   12.2677    2.4709    0.1341   78.9444   -1.1120   49.0000 
+2640.6250    8.5000    8.8254   43.8987   12.5675    2.4558    0.1272   78.7005   -1.6462   49.0000 
+2640.7250    8.5000    8.8499   44.8668   13.0805    2.4433    0.1215   78.3923   -2.0831   49.0000 
+2640.8250    8.5000    8.8254   46.8335   13.8373    2.4340    0.1184   78.0694   -2.3740   49.0000 
+2640.9250    8.5000    8.8335   50.0602   14.7631    2.4288    0.1162   77.7949   -2.5530   49.0000 
+2641.0250    8.5000    8.8663   52.9950   15.6342    2.4309    0.1144   77.4908   -2.5680   49.0000 
+2641.1250    8.5000    8.8499   54.5623   16.1011    2.4432    0.1134   77.3464   -2.3572   49.0000 
+2641.2250    8.5000    8.8499   56.0834   16.0134    2.4611    0.1130   77.4423   -2.0119   49.0000 
+2641.3250    8.5000    8.8254   55.5764   15.5809    2.4834    0.1131   77.6464   -1.5602   49.0000 
+2641.4250    8.5000    8.8499   53.2716   15.1764    2.5038    0.1124   77.7730   -1.1762   49.0000 
+2641.5250    8.5000    8.8581   49.8605   15.1219    2.5151    0.1105   77.3000   -1.0153   49.0000 
+2641.6250    8.5000    8.8417   44.9052   15.6702    2.5123    0.1054   76.4128   -1.2418   49.0000 
+2641.7250    8.5000    8.8663   40.4185   17.0925    2.4963    0.0994   75.4464   -1.7600   49.0000 
+2641.8250    8.5000    8.8172   38.1905   19.6782    2.4797    0.0972   74.6434   -2.1663   49.0000 
+2641.9250    8.5000    8.7845   39.0740   23.4979    2.4651    0.1052   74.2806   -2.1928   49.0000 
+2642.0250    8.5000    8.7926   43.5453   27.5735    2.4489    0.1222   74.2270   -1.9481   49.0000 
+2642.1250    8.5000    8.7763   50.0833   29.1037    2.4320    0.1401   74.6240   -1.6889   49.0000 
+2642.2250    8.5000    8.8090   57.5431   26.1537    2.4196    0.1504   75.2862   -1.5959   49.0000 
+2642.3250    8.5000    8.8254   63.5664   21.0571    2.4244    0.1535   76.3964   -1.3969   49.0000 
+2642.4250    8.5000    8.8254   66.4627   16.8407    2.4316    0.1533   77.6653   -1.2591   49.0000 
+2642.5250    8.5000    8.7926   66.6778   14.3579    2.4376    0.1542   78.8628   -1.1092   49.0000 
+2642.6250    8.5000    8.7926   64.9108   13.2782    2.4300    0.1528   79.8000   -1.3072   49.0000 
+2642.7250    8.5000    8.8172   62.2834   13.1057    2.4259    0.1496   80.1454   -1.4952   49.0000 
+2642.8250    8.5000    8.8335   60.4626   13.3465    2.4294    0.1434   80.2128   -1.6317   49.0000 
+2642.9250    8.5000    8.8663   59.4869   13.6382    2.4405    0.1388   80.0418   -1.5628   49.0000 
+2643.0250    8.5000    8.8417   57.4586   13.7754    2.4513    0.1358   79.8260   -1.4482   49.0000 
+2643.1250    8.5000    8.8417   55.9912   13.7366    2.4506    0.1351   79.4510   -1.4869   49.0000 
+2643.2250    8.5000    8.8172   55.2307   13.5938    2.4501    0.1343   78.9128   -1.5199   49.0000 
+2643.3250    8.5000    8.8335   55.2230   13.3806    2.4509    0.1333   78.2383   -1.5393   49.0000 
+2643.4250    8.5000    8.8417   57.6507   13.0969    2.4652    0.1327   77.6500   -1.2706   49.0000 
+2643.5250    8.5000    8.8663   60.8390   12.7488    2.4748    0.1335   77.2245   -1.0542   49.0000 
+2643.6250    8.5000    8.8581   63.0900   12.3925    2.4782    0.1356   77.0689   -0.9164   25.0000 
+2643.7250    8.5000    8.8499   64.4883   12.1233    2.4658    0.1367   77.2179   -1.1286   49.0000 
+2643.8250    8.5000    8.8172   64.1426   12.0140    2.4592    0.1373   77.4827   -1.2417   49.0000 
+2643.9250    8.5000    8.8254   62.5138   12.0916    2.4628    0.1370   77.7061   -1.1780   49.0000 
+2644.0250    8.5000    8.8335   62.6752   12.3102    2.4809    0.1363   77.6439   -0.8371   25.0000 
+2644.1250    8.5000    8.8499   65.4563   12.5984    2.5003    0.1347   77.2520   -0.5037   25.0000 
+2644.2250    8.5000    8.8663   69.3514   12.8415    2.5174    0.1329   76.6204   -0.2211   54.0000 
+2644.3250    8.5000    8.8826   74.4373   12.9062    2.5295    0.1340   76.0372    0.0556   54.0000 
+2644.4250    8.5000    8.8744   77.2492   12.7021    2.5338    0.1374   75.7525    0.2561   54.0000 
+2644.5250    8.5000    8.8663   77.3106   12.3147    2.5274    0.1422   75.6520    0.2864   54.0000 
+2644.6250    8.5000    8.8417   77.3337   11.8948    2.5168    0.1444   75.7597    0.1471   54.0000 
+2644.7250    8.5000    8.8172   76.7421   11.5616    2.5151    0.1438   75.5842    0.0958   54.0000 
+2644.8250    8.5000    8.8008   77.7793   11.3303    2.5212    0.1440   75.2342    0.2261   54.0000 
+2644.9250    8.5000    8.8417   79.6769   11.1942    2.5357    0.1465   74.6954    0.5987   57.0000 
+2645.0250    8.5000    8.8417   80.3453   11.1400    2.5438    0.1502   74.0582    0.8833   57.0000 
+2645.1250    8.5000    8.8254   80.5758   11.1718    2.5488    0.1498   73.5071    0.9695   57.0000 
+2645.2250    8.5000    8.8335   78.5091   11.3060    2.5431    0.1462   72.8755    0.7367   57.0000 
+2645.3250    8.5000    8.8172   73.2081   11.5893    2.5334    0.1410   72.0383    0.3697   57.0000 
+2645.4250    8.5000    8.8172   67.7304   12.1315    2.5189    0.1352   70.9097   -0.1151   54.0000 
+2645.5250    8.5000    8.8090   60.1553   13.0938    2.5025    0.1258   69.5051   -0.7565   25.0000 
+2645.6250    8.5000    8.7763   52.7953   14.6985    2.4917    0.1113   68.1582   -1.4562   49.0000 
+2645.7250    8.5000    8.7681   47.8476   17.2680    2.4929    0.0948   67.2704   -1.9827   49.0000 
+2645.8250    8.5000    8.7763   42.8232   21.1797    2.5003    0.0819   66.9918   -2.2636   49.0000 
+2645.9250    8.5000    8.7681   40.2111   26.6968    2.4980    0.0762   67.5112   -2.5014   49.0000 
+2646.0250    8.5000    8.8008   38.8512   33.2472    2.4779    0.0763   68.5714   -2.8991   49.0000 
+2646.1250    8.5000    8.8090   37.4760   40.3743    2.4511    0.0786   69.7898   -3.3558   49.0000 
+2646.2250    8.5000    8.8254   36.9306   46.2841    2.4322    0.0807   70.9480   -3.6650   49.0000 
+2646.3250    8.5000    8.8417   36.3928   50.2003    2.4264    0.0819   71.6755   -3.7414   49.0000 
+2646.4250    8.5000    8.8335   35.3863   52.7425    2.4258    0.0817   72.0214   -3.7603   49.0000 
+2646.5250    8.5000    8.8335   34.6642   54.6756    2.4221    0.0806   71.8796   -3.8690   49.0000 
+2646.6250    8.5000    8.8172   35.2020   56.7958    2.4198    0.0785   71.4949   -3.9896   49.0000 
+2646.7250    8.5000    8.8254   36.2314   58.6193    2.4234    0.0764   70.9694   -3.9845   49.0000 
+2646.8250    8.5000    8.8172   38.5362   59.4472    2.4355    0.0732   70.6566   -3.8489   49.0000 
+2646.9250    8.5000    8.8172   41.8321   58.8100    2.4470    0.0699   70.6577   -3.7281   49.0000 
+2647.0250    8.5000    8.8172   44.9974   56.9989    2.4545    0.0669   71.1663   -3.6797   49.0000 
+2647.1250    8.5000    8.8172   47.6709   53.8573    2.4533    0.0668   72.1888   -3.7067   49.0000 
+2647.2250    8.5000    8.8335   48.8080   48.5344    2.4436    0.0699   73.4735   -3.7996   49.0000 
+2647.3250    8.5000    8.8172   49.1921   42.4257    2.4332    0.0763   74.8265   -3.7928   49.0000 
+2647.4250    8.5000    8.8254   49.0999   35.1114    2.4332    0.0850   75.9485   -3.5016   49.0000 
+2647.5250    8.5000    8.8417   50.5750   28.5051    2.4449    0.0955   76.7367   -2.9169   49.0000 
+2647.6250    8.5000    8.8417   53.5405   23.2589    2.4610    0.1056   77.3061   -2.2607   49.0000 
+2647.7250    8.5000    8.8499   56.5367   19.6032    2.4699    0.1130   77.9138   -1.8345   49.0000 
+2647.8250    8.5000    8.8090   57.9273   17.2289    2.4671    0.1175   78.7801   -1.7399   49.0000 
+2647.9250    8.5000    8.8172   56.1833   15.8663    2.4531    0.1213   79.9087   -1.8943   49.0000 
+2648.0250    8.5000    8.8254   53.0718   15.2617    2.4363    0.1255   80.8531   -2.0918   49.0000 
+2648.1250    8.5000    8.8254   50.5366   15.2854    2.4245    0.1288   81.2893   -2.2167   49.0000 
+2648.2250    8.5000    8.8581   50.0141   15.7171    2.4180    0.1295   81.1622   -2.3250   49.0000 
+2648.3250    8.5000    8.8172   52.0577   16.2475    2.4157    0.1290   80.6418   -2.3880   49.0000 
+2648.4250    8.5000    8.8335   56.0143   16.4193    2.4249    0.1293   80.0102   -2.1910   49.0000 
+2648.5250    8.5000    8.8417   59.0797   15.9846    2.4425    0.1302   79.3612   -1.8088   49.0000 
+2648.6250    8.5000    8.8663   60.4472   15.0876    2.4598    0.1313   78.9107   -1.4284   49.0000 
+2648.7250    8.5000    8.8826   59.6405   14.1335    2.4598    0.1313   78.7816   -1.4279   49.0000 
+2648.8250    8.5000    8.8908   56.4215   13.4417    2.4514    0.1317   79.0949   -1.5820   49.0000 
+2648.9250    8.5000    8.8990   52.8260   13.1307    2.4431    0.1323   79.6077   -1.7291   49.0000 
+2649.0250    8.5000    8.8826   50.7670   13.1207    2.4450    0.1338   79.9566   -1.6392   49.0000 
+2649.1250    8.5000    8.8663   50.4751   13.2375    2.4510    0.1361   80.1709   -1.4417   49.0000 
+2649.2250    8.5000    8.8499   51.3893   13.3057    2.4548    0.1386   80.1551   -1.2850   49.0000 
+2649.3250    8.5000    8.8335   52.4649   13.2535    2.4535    0.1402   80.2750   -1.2549   49.0000 
+2649.4250    8.5000    8.8254   51.9732   13.1480    2.4449    0.1404   80.5128   -1.4213   49.0000 
+2649.5250    8.5000    8.8581   50.9745   13.1175    2.4413    0.1390   80.9362   -1.5429   49.0000 
+2649.6250    8.5000    8.8499   50.1447   13.2302    2.4365    0.1374   81.3561   -1.6878   49.0000 
+2649.7250    8.5000    8.8826   50.8131   13.4033    2.4395    0.1360   81.6388   -1.6751   49.0000 
+2649.8250    8.5000    8.9153   53.4867   13.4652    2.4415    0.1353   81.6745   -1.6585   49.0000 
+2649.9250    8.5000    8.8826   57.3511   13.2819    2.4538    0.1343   81.3311   -1.4482   49.0000 
+2650.0250    8.5000    8.8826   61.3768   12.8817    2.4730    0.1336   80.7485   -1.0880   49.0000 
+2650.1250    8.5000    8.8990   64.3346   12.3981    2.4964    0.1354   79.9526   -0.5587   25.0000 
+2650.2250    8.5000    8.9235   65.9633   11.9575    2.5166    0.1369   79.2985   -0.1065   54.0000 
+2650.3250    8.5000    8.9399   65.0568   11.6622    2.5182    0.1388   78.9867   -0.0092   54.0000 
+2650.4250    8.5000    8.9481   63.4127   11.6189    2.5003    0.1363   79.2219   -0.4486   25.0000 
+2650.5250    8.5000    8.8744   61.7763   11.9506    2.4629    0.1350   79.7046   -1.2433   49.0000 
+2650.6250    8.5000    8.8499   59.9171   12.7122    2.4307    0.1308   80.1316   -2.0252   49.0000 
+2650.7250    8.5000    8.8581   59.0950   13.8272    2.4133    0.1276   80.1944   -2.4801   49.0000 
+2650.8250    8.5000    8.8335   57.7122   15.0101    2.4207    0.1235   79.9281   -2.4700   49.0000 
+2650.9250    8.5000    8.8417   55.8222   15.7858    2.4382    0.1221   79.4408   -2.1679   49.0000 
+2651.0250    8.5000    8.8335   55.2230   15.7871    2.4604    0.1223   78.8306   -1.7147   49.0000 
+2651.1250    8.5000    8.8581   56.1449   15.0550    2.4720    0.1246   78.2332   -1.4050   49.0000 
+2651.2250    8.5000    8.8990   58.5265   14.0089    2.4798    0.1285   77.7985   -1.1220   49.0000 
+2651.3250    8.5000    8.9153   60.8313   13.0403    2.4830    0.1338   77.7577   -0.8803   25.0000 
+2651.4250    8.5000    8.8908   61.5535   12.3718    2.4823    0.1401   78.1811   -0.6835   25.0000 
+2651.5250    8.5000    8.8581   60.3396   12.0594    2.4670    0.1450   78.8005   -0.8268   25.0000 
+2651.6250    8.5000    8.8417   58.8799   12.0473    2.4389    0.1477   79.4383   -1.2993   49.0000 
+2651.7250    8.5000    8.8417   58.8722   12.2196    2.4111    0.1486   79.8852   -1.8259   49.0000 
+2651.8250    8.5000    8.8335   59.5560   12.4522    2.3995    0.1503   80.0648   -1.9989   49.0000 
+2651.9250    8.5000    8.8254   60.4933   12.6788    2.3978    0.1531   80.1423   -1.9417   49.0000 
+2652.0250    8.5000    8.8090   60.8928   12.8655    2.3966    0.1551   80.1199   -1.8979   49.0000 
+2652.1250    8.5000    8.8254   60.0246   12.9999    2.3852    0.1556   80.2633   -2.1088   49.0000 
+2652.2250    8.5000    8.8581   58.7032   13.0498    2.3733    0.1548   80.4561   -2.3735   49.0000 
+2652.3250    8.5000    8.8663   59.1181   12.9780    2.3718    0.1535   80.5490   -2.4461   49.0000 
+2652.4250    8.5000    8.8744   59.9939   12.7597    2.3887    0.1517   80.2944   -2.1683   49.0000 
+2652.5250    8.5000    8.8581   61.9530   12.4095    2.4190    0.1498   79.7225   -1.6252   49.0000 
+2652.6250    8.5000    8.8581   64.6112   11.9945    2.4471    0.1487   79.0980   -1.1007   49.0000 
+2652.7250    8.5000    8.8499   65.2873   11.6152    2.4624    0.1481   78.7709   -0.8164   25.0000 
+2652.8250    8.5000    8.8908   65.7021   11.3672    2.4567    0.1488   78.6923   -0.9050   25.0000 
+2652.9250    8.5000    8.8744   65.1106   11.2995    2.4424    0.1480   78.7811   -1.2172   49.0000 
+2653.0250    8.5000    8.8990   65.8942   11.4169    2.4292    0.1456   78.6806   -1.5611   49.0000 
+2653.1250    8.5000    8.9235   68.1529   11.7223    2.4354    0.1402   78.2577   -1.6182   49.0000 
+2653.2250    8.5000    8.8990   70.8956   12.2872    2.4541    0.1358   77.4980   -1.3905   49.0000 
+2653.3250    8.5000    8.8990   74.0148   13.2811    2.4691    0.1332   76.4286   -1.1764   49.0000 
+2653.4250    8.5000    8.8826   73.5154   14.9365    2.4688    0.1320   75.2531   -1.2218   49.0000 
+2653.5250    8.5000    8.8417   70.4961   17.4709    2.4528    0.1290   74.3153   -1.6438   49.0000 
+2653.6250    8.5000    8.8499   64.9723   21.0633    2.4375    0.1212   73.7531   -2.2080   49.0000 
+2653.7250    8.5000    8.8417   57.3204   25.8984    2.4251    0.1097   73.7071   -2.8397   49.0000 
+2653.8250    8.5000    8.8663   50.8976   31.8980    2.4164    0.0982   73.8235   -3.3977   49.0000 
+2653.9250    8.5000    8.8744   45.2739   38.1232    2.4047    0.0916   73.8245   -3.8526   49.0000 
+2654.0250    8.5000    8.8581   41.4864   42.3170    2.3931    0.0910   73.7066   -4.1030   49.0000 
+2654.1250    8.5000    8.8417   40.1803   43.6932    2.3911    0.0947   73.5776   -4.0226   49.0000 
+2654.2250    8.5000    8.8254   39.3967   43.4702    2.4078    0.0987   73.7745   -3.5529   49.0000 
+2654.3250    8.5000    8.8172   39.1355   42.1362    2.4325    0.1011   74.2082   -2.9805   49.0000 
+2654.4250    8.5000    8.8335   39.5196   39.4151    2.4511    0.1003   74.5102   -2.6335   49.0000 
+2654.5250    8.5000    8.8663   41.5171   34.8069    2.4548    0.0993   74.6184   -2.5920   49.0000 
+2654.6250    8.5000    8.8908   46.0499   29.0016    2.4595    0.1012   74.6735   -2.4374   49.0000 
+2654.7250    8.5000    8.8990   52.8106   23.5609    2.4681    0.1085   74.8444   -2.0202   49.0000 
+2654.8250    8.5000    8.8744   59.6943   19.6196    2.4751    0.1193   75.2000   -1.5226   49.0000 
+2654.9250    8.5000    8.8663   63.3973   17.4549    2.4650    0.1296   75.3439   -1.3787   49.0000 
+2655.0250    8.5000    8.8663   63.2053   16.9031    2.4468    0.1348   75.2959   -1.5708   49.0000 
+2655.1250    8.5000    8.8663   59.5714   17.7548    2.4292    0.1346   75.1071   -1.9302   49.0000 
+2655.2250    8.5000    8.9072   54.3933   19.7807    2.4241    0.1291   74.9439   -2.2151   49.0000 
+2655.3250    8.5000    8.8990   49.2151   22.6233    2.4242    0.1217   74.6990   -2.4585   49.0000 
+2655.4250    8.5000    8.8908   44.9282   25.6334    2.4271    0.1144   74.3112   -2.6439   49.0000 
+2655.5250    8.5000    8.8826   42.1548   27.7512    2.4278    0.1090   74.1005   -2.8125   49.0000 
+2655.6250    8.5000    8.8254   41.0946   28.1631    2.4326    0.1064   74.2444   -2.8012   49.0000 
+2655.7250    8.5000    8.8335   42.5235   26.4738    2.4383    0.1070   74.9311   -2.6667   49.0000 
+2655.8250    8.5000    8.8008   46.4494   23.3031    2.4491    0.1113   75.9378   -2.3088   49.0000 
+2655.9250    8.5000    8.8172   51.7581   19.8059    2.4555    0.1187   76.9459   -1.9315   49.0000 
+2656.0250    8.5000    8.8090   56.6673   16.7596    2.4639    0.1271   77.8811   -1.4841   49.0000 
+2656.1250    8.5000    8.8254   60.0323   14.6147    2.4632    0.1345   78.6219   -1.2535   49.0000 
+2656.2250    8.5000    8.8499   61.6764   13.3360    2.4588    0.1395   79.0980   -1.1739   49.0000 
+2656.3250    8.5000    8.8335   62.4831   12.7396    2.4473    0.1427   79.2735   -1.2987   49.0000 
+2656.4250    8.5000    8.8744   62.5138   12.5846    2.4402    0.1447   79.1143   -1.3729   49.0000 
+2656.5250    8.5000    8.8744   62.7750   12.6993    2.4359    0.1457   78.7597   -1.4236   49.0000 
+2656.6250    8.5000    8.8908   64.1426   12.9535    2.4413    0.1457   78.2077   -1.3193   49.0000 
+2656.7250    8.5000    8.9153   65.8404   13.3592    2.4506    0.1453   77.3929   -1.1432   49.0000 
+2656.8250    8.5000    8.8663   67.6996   14.0243    2.4658    0.1443   76.3663   -0.8723   25.0000 
+2656.9250    8.5000    8.8663   68.3911   15.1982    2.4677    0.1428   75.1908   -0.8856   25.0000 
+2657.0250    8.5000    8.8663   66.0632   17.1273    2.4591    0.1374   74.0495   -1.2377   49.0000 
+2657.1250    8.5000    8.8581   60.9389   19.9938    2.4436    0.1266   73.2056   -1.9069   49.0000 
+2657.2250    8.5000    8.9072   55.5841   23.5082    2.4433    0.1111   72.6658   -2.4319   49.0000 
+2657.3250    8.5000    8.9072   51.0359   26.6617    2.4641    0.0952   72.4189   -2.5433   49.0000 
+2657.4250    8.5000    8.9153   48.2394   28.5712    2.4924    0.0842   72.4842   -2.3474   49.0000 
+2657.5250    8.5000    8.8990   47.6940   29.0976    2.5084    0.0790   72.7577   -2.1995   49.0000 
+2657.6250    8.5000    8.8990   47.9706   29.0077    2.4969    0.0798   73.2903   -2.4030   49.0000 
+2657.7250    8.5000    8.9399   48.8617   29.0826    2.4687    0.0829   73.8265   -2.8614   49.0000 
+2657.8250    8.5000    8.9644   50.0372   29.5732    2.4454    0.0871   74.1122   -3.1891   49.0000 
+2657.9250    8.5000    8.9644   50.4444   30.3224    2.4348    0.0886   74.0306   -3.3519   49.0000 
+2658.0250    8.5000    8.9481   50.3138   30.9208    2.4386    0.0874   73.6066   -3.3160   49.0000 
+2658.1250    8.5000    8.8826   50.2216   30.6275    2.4459    0.0847   73.0500   -3.2567   49.0000 
+2658.2250    8.5000    8.9072   50.6672   28.6866    2.4664    0.0839   72.6939   -2.8755   49.0000 
+2658.3250    8.5000    8.9399   52.4880   25.2007    2.4985    0.0866   72.7480   -2.1431   49.0000 
+2658.4250    8.5000    8.9644   55.6071   21.1665    2.5339    0.0936   73.4408   -1.1999   49.0000 
+2658.5250    8.5000    8.9808   59.5099   17.8657    2.5462    0.1046   74.5388   -0.5913   25.0000 
+2658.6250    8.5000    8.9808   62.5868   15.7269    2.5303    0.1172   75.8122   -0.4857   25.0000 
+2658.7250    8.5000    8.9644   65.1375   14.5850    2.4967    0.1276   77.0117   -0.8135   25.0000 
+2658.8250    8.5000    8.9808   66.1362   14.1986    2.4688    0.1326   78.0041   -1.2036   49.0000 
+2658.9250    8.5000    9.0053   65.3833   14.2838    2.4534    0.1323   78.5959   -1.5239   49.0000 
+2659.0250    8.5000    8.9808   64.7610   14.6662    2.4541    0.1278   78.2903   -1.6585   49.0000 
+2659.1250    8.5000    8.9726   64.6688   15.2086    2.4668    0.1225   76.9464   -1.5799   49.0000 
+2659.2250    8.5000    8.9562   66.0056   15.8251    2.4875    0.1178   74.8699   -1.3239   49.0000 
+2659.3250    8.5000    8.9644   68.7253   16.4018    2.5125    0.1157   72.9281   -0.8929   25.0000 
+2659.4250    8.5000    8.9562   72.3707   16.8679    2.5391    0.1150   71.9638   -0.3851   25.0000 
+2659.5250    8.5000    8.9644   75.5820   17.2921    2.5678    0.1142   72.0179    0.1629   54.0000 
+2659.6250    8.5000    8.9890   77.5334   17.9300    2.5823    0.1121   72.3781    0.3826   57.0000 
+2659.7250    8.5000    8.9317   78.1788   19.1457    2.5841    0.1080   72.3622    0.2824   54.0000 
+2659.8250    8.5000    8.8744   76.1659   21.3633    2.5696    0.1030   71.6918   -0.1730   54.0000 
+2659.9250    8.5000    8.7845   71.0185   24.7474    2.5560    0.0974   70.8801   -0.6350   25.0000 
+2660.0250    8.5000    8.7027   64.8494   28.3806    2.5393    0.0921   70.5740   -1.1448   49.0000 
+2660.1250    8.5000    8.6945   59.0874   29.9380    2.5282    0.0896   70.9107   -1.4488   49.0000 
+2660.2250    8.5000    8.7027   56.2525   27.8540    2.5274    0.0921   71.8526   -1.3831   49.0000 
+2660.3250    8.5000    8.6863   58.7954   24.2508    2.5378    0.1017   73.1235   -0.8563   25.0000 
+2660.4250    8.5000    8.6781   64.9416   21.5024    2.5522    0.1159   74.3041   -0.0924   54.0000 
+2660.5250    8.5000    8.6618   71.0262   20.5820    2.5568    0.1305   75.1439    0.4860   57.0000 
+2660.6250    8.5000    8.6618   75.0212   21.5147    2.5538    0.1379   75.2546    0.6746   57.0000 
+2660.7250    8.5000    8.6454   75.1134   24.7217    2.5381    0.1355   74.8240    0.2776   54.0000 
+2660.8250    8.5000    8.6454   71.2874   31.8097    2.5115    0.1258   74.0944   -0.5749   25.0000 
+2660.9250    8.5000    8.6372   66.5088   45.8476    2.4727    0.1154   73.6250   -1.6995   49.0000 
+2661.0250    8.5000    8.6372   61.5304   64.8182    2.4380    0.1079   73.3378   -2.6430   49.0000 
+2661.1250    8.5000    8.6699   55.4996   71.7392    2.4159    0.1027   73.2699   -3.2584   49.0000 
+2661.2250    8.5000    8.6699   50.4597   63.8419    2.4115    0.0991   73.3393   -3.4680   49.0000 
+2661.3250    8.5000    8.6699   46.5569   60.3354    2.4149    0.0980   73.5015   -3.4345   49.0000 
+2661.4250    8.5000    8.6781   44.8668   62.5097    2.4182    0.1002   73.9801   -3.2974   49.0000 
+2661.5250    8.5000    8.6372   46.4494   64.2677    2.4163    0.1044   74.6515   -3.1938   49.0000 
+2661.6250    8.5000    8.6454   48.3316   60.6673    2.4116    0.1096   75.3811   -3.1129   49.0000 
+2661.7250    8.5000    8.6618   50.9053   53.0236    2.4057    0.1157   76.0801   -3.0289   49.0000 
+2661.8250    8.5000    8.6699   52.3881   44.0058    2.4027    0.1216   76.5561   -2.8911   49.0000 
+2661.9250    8.5000    8.7027   54.0475   36.4404    2.4055    0.1258   76.8163   -2.6964   49.0000 
+2662.0250    8.5000    8.7108   57.4894   31.2141    2.4188    0.1291   76.9750   -2.3216   49.0000 
+2662.1250    8.5000    8.7108   60.9927   28.4424    2.4337    0.1320   76.9740   -1.9273   49.0000 
+2662.2250    8.5000    8.6863   64.1118   28.2935    2.4392    0.1339   76.9883   -1.7520   49.0000 
+2662.3250    8.5000    8.6536   65.2335   30.9869    2.4339    0.1320   77.0005   -1.9210   49.0000 
+2662.4250    8.5000    8.6372   63.3436   37.0505    2.4255    0.1272   77.0918   -2.2497   49.0000 
+2662.5250    8.5000    8.5800   59.8018   46.7895    2.4183    0.1205   77.2510   -2.6178   49.0000 
+2662.6250    8.5000    8.5881   55.5764   59.4874    2.4103    0.1148   77.2367   -2.9677   49.0000 
+2662.7250    8.5000    8.5881   51.2895   73.2231    2.4010    0.1100   76.9015   -3.3146   49.0000 
+2662.8250    8.5000    8.6045   48.0166   85.9470    2.3930    0.1070   76.4495   -3.5725   49.0000 
+2662.9250    8.5000    8.6290   45.1741   94.9174    2.3862    0.1057   76.1352   -3.7518   49.0000 
+2663.0250    8.5000    8.6127   44.1138   92.2927    2.3822    0.1059   75.9903   -3.8262   49.0000 
+2663.1250    8.5000    8.6209   45.0819   80.4891    2.3811    0.1070   76.0265   -3.8111   49.0000 
+2663.2250    8.5000    8.6127   48.1857   66.6259    2.3783    0.1085   76.0893   -3.8164   49.0000 
+2663.3250    8.5000    8.6209   52.3497   57.5371    2.3731    0.1103   76.2633   -3.8614   49.0000 
+2663.4250    8.5000    8.6536   56.3216   52.1017    2.3670    0.1123   76.7959   -3.9169   49.0000 
+2663.5250    8.5000    8.6454   58.3037   49.7556    2.3702    0.1143   77.3806   -3.7869   49.0000 
+2663.6250    8.5000    8.6618   56.9900   49.5260    2.3726    0.1156   77.9612   -3.6932   49.0000 
+2663.7250    8.5000    8.6454   54.8389   50.6081    2.3743    0.1166   78.5214   -3.6273   49.0000 
+2663.8250    8.5000    8.6536   51.5737   51.4859    2.3682    0.1167   78.9944   -3.7468   49.0000 
+2663.9250    8.5000    8.6536   49.8221   50.5103    2.3692    0.1172   79.3235   -3.7112   49.0000 
+2664.0250    8.5000    8.6536   50.8823   47.9834    2.3732    0.1169   79.2786   -3.6399   49.0000 
+2664.1250    8.5000    8.6536   52.5725   45.5838    2.3794    0.1178   78.6270   -3.4847   49.0000 
+2664.2250    8.5000    8.6454   54.0245   44.7687    2.3814    0.1193   77.8607   -3.3946   49.0000 
+2664.3250    8.5000    8.6536   53.3791   45.6793    2.3786    0.1228   77.4005   -3.3327   49.0000 
+2664.4250    8.5000    8.6699   50.6825   47.0908    2.3764    0.1261   77.2311   -3.2702   49.0000 
+2664.5250    8.5000    8.6618   47.9475   46.6145    2.3733    0.1278   77.2071   -3.2723   49.0000 
+2664.6250    8.5000    8.6618   46.6875   43.1562    2.3739    0.1278   77.0189   -3.2606   49.0000 
+2664.7250    8.5000    8.6209   47.6978   38.3254    2.3809    0.1270   76.9505   -3.1498   49.0000 
+2664.8250    8.5000    8.5963   50.1409   34.2728    2.3976    0.1272   77.2612   -2.8093   49.0000 
+2664.9250    8.5000    8.6045   51.8925   32.0024    2.4175    0.1283   78.0908   -2.3740   49.0000 
+2665.0250    8.5000    8.6290   52.6608   31.7832    2.4273    0.1317   79.0398   -2.0646   49.0000 
+2665.1250    8.5000    8.6536   52.4380   33.7814    2.4175    0.1353   79.6969   -2.1382   49.0000 
+2665.2250    8.5000    8.6618   51.0859   38.4722    2.3966    0.1364   79.7995   -2.5200   49.0000 
+2665.3250    8.5000    8.6699   48.8733   46.3592    2.3730    0.1321   79.3653   -3.1353   49.0000 
+2665.4250    8.5000    8.6863   46.6991   57.7561    2.3612    0.1234   78.7832   -3.6645   49.0000 
+2665.5250    8.5000    8.6781   44.2137   71.6797    2.3569    0.1153   78.4474   -4.0187   49.0000 
+2665.6250    8.5000    8.6536   41.9089   87.0292    2.3614    0.1113   78.5684   -4.0629   49.0000 
+2665.7250    8.5000    8.6290   41.2636  102.4319    2.3622    0.1113   78.7954   -4.0450   49.0000 
+2665.8250    8.5000    8.6290   40.5568  117.8564    2.3588    0.1126   78.9372   -4.0712   49.0000 
+2665.9250    8.5000    8.6045   40.1803  129.5779    2.3482    0.1134   78.7878   -4.2545   49.0000 
+2666.0250    8.5000    8.5963   40.0036  133.8062    2.3427    0.1145   78.6908   -4.3295   49.0000 
+2666.1250    8.5000    8.5881   38.7667  132.0943    2.3390    0.1167   78.8760   -4.3303   49.0000 
+2666.2250    8.5000    8.5963   38.0906  126.0206    2.3416    0.1206   79.2321   -4.1491   49.0000 
+2666.3250    8.5000    8.6290   37.3454  118.5450    2.3403    0.1242   79.5878   -4.0515   49.0000 
+2666.4250    8.5000    8.6372   37.2532  113.6332    2.3444    0.1260   79.5811   -3.9114   49.0000 
+2666.5250    8.5000    8.6699   38.6668  111.8820    2.3470    0.1248   79.3750   -3.8988   49.0000 
+2666.6250    8.5000    8.6945   39.5734  112.9068    2.3516    0.1244   79.1454   -3.8208   49.0000 
+2666.7250    8.5000    8.7108   41.2405  114.7607    2.3543    0.1250   78.9791   -3.7480   49.0000 
+2666.8250    8.5000    8.7272   42.9999  116.3976    2.3574    0.1260   78.8571   -3.6514   49.0000 
+2666.9250    8.5000    8.6945   43.5607  115.5913    2.3623    0.1251   78.6617   -3.5828   49.0000 
+2667.0250    8.5000    8.6454   44.4980  113.7763    2.3626    0.1233   78.3291   -3.6384   49.0000 
+2667.1250    8.5000    8.6290   45.2202  111.0495    2.3606    0.1229   77.9811   -3.6932   49.0000 
+2667.2250    8.5000    8.6127   45.4045  108.3218    2.3536    0.1238   77.6179   -3.8011   49.0000 
+2667.3250    8.5000    8.6618   46.3879  105.2306    2.3484    0.1261   77.2077   -3.8292   49.0000 
+2667.4250    8.5000    8.6699   47.2176  102.3818    2.3423    0.1281   76.9587   -3.8825   49.0000 
+2667.5250    8.5000    8.6699   47.2906  100.9642    2.3374    0.1297   76.7505   -3.9295   49.0000 
+2667.6250    8.5000    8.6781   46.6760   99.0400    2.3364    0.1294   76.8367   -3.9578   49.0000 
+2667.7250    8.5000    8.6536   44.4480   96.2965    2.3371    0.1278   77.1071   -3.9966   49.0000 
+2667.8250    8.5000    8.6536   42.4813   91.7823    2.3413    0.1255   77.3878   -3.9903   49.0000 
+2667.9250    8.5000    8.6618   41.8820   87.9925    2.3438    0.1244   77.4235   -3.9777   49.0000 
+2668.0250    8.5000    8.6536   43.4109   85.7038    2.3563    0.1231   76.8439   -3.7706   49.0000 
+2668.1250    8.5000    8.6372   46.5761   84.9593    2.3749    0.1203   75.6439   -3.4924   49.0000 
+2668.2250    8.5000    8.6454   49.4648   85.2341    2.4077    0.1150   73.9337   -3.0129   49.0000 
+2668.3250    8.5000    8.6045   51.2587   86.1400    2.4454    0.1098   72.1806   -2.4339   49.0000 
+2668.4250    8.5000    8.6290   51.5046   87.4877    2.4871    0.1055   70.8071   -1.7411   49.0000 
+2668.5250    8.5000    8.5963   51.9348   88.0106    2.5098    0.1027   70.1561   -1.3812   49.0000 
+2668.6250    8.5000    8.6290   52.4880   86.4217    2.5043    0.1012   70.4673   -1.5396   49.0000 
+2668.7250    8.5000    8.6290   52.5417   82.1002    2.4702    0.1025   71.8219   -2.1802   49.0000 
+2668.8250    8.5000    8.6372   51.8887   77.5347    2.4275    0.1069   73.9995   -2.8854   49.0000 
+2668.9250    8.5000    8.6454   49.9604   75.4505    2.3910    0.1139   76.3464   -3.3833   49.0000 
+2669.0250    8.5000    8.6454   48.3163   76.3009    2.3706    0.1202   78.2475   -3.5804   49.0000 
+2669.1250    8.5000    8.6536   46.9872   79.1615    2.3649    0.1237   79.3801   -3.5792   49.0000 
+2669.2250    8.5000    8.6454   45.6965   82.3740    2.3667    0.1229   79.7495   -3.5713   49.0000 
+2669.3250    8.5000    8.6781   44.6824   85.5977    2.3666    0.1202   79.6158   -3.6618   49.0000 
+2669.4250    8.5000    8.6699   42.5927   88.4687    2.3636    0.1172   79.2347   -3.8212   49.0000 
+2669.5250    8.5000    8.6699   40.7796   90.4950    2.3579    0.1153   78.8622   -3.9968   49.0000 
+2669.6250    8.5000    8.6863   40.2648   91.0199    2.3532    0.1149   78.7296   -4.1051   49.0000 
+2669.7250    8.5000    8.6536   40.0958   90.0253    2.3450    0.1159   78.8592   -4.2346   49.0000 
+2669.8250    8.5000    8.6699   41.3250   88.2903    2.3389    0.1171   79.1439   -4.3194   49.0000 
+2669.9250    8.5000    8.6536   43.3763   85.6206    2.3337    0.1167   79.3316   -4.4337   49.0000 
+2670.0250    8.5000    8.6945   45.9961   83.0605    2.3335    0.1157   79.3469   -4.4724   49.0000 
+2670.1250    8.5000    8.6781   49.4994   80.5135    2.3382    0.1158   79.1102   -4.3755   49.0000 
+2670.2250    8.5000    8.6863   52.9259   77.9815    2.3452    0.1166   78.7684   -4.2076   49.0000 
+2670.3250    8.5000    8.6536   55.1538   76.2294    2.3564    0.1168   78.6107   -3.9797   49.0000 
+2670.4250    8.5000    8.6127   55.5610   75.0654    2.3632    0.1150   78.5913   -3.9008   49.0000 
+2670.5250    8.5000    8.6209   54.4624   75.7169    2.3703    0.1142   78.7995   -3.7876   49.0000 
+2670.6250    8.5000    8.5963   51.4047   77.4466    2.3712    0.1143   78.9429   -3.7656   49.0000 
+2670.7250    8.5000    8.6127   48.0858   81.1290    2.3703    0.1158   78.9735   -3.7343   49.0000 
+2670.8250    8.5000    8.6372   45.9270   85.4580    2.3635    0.1156   79.0224   -3.8760   49.0000 
+2670.9250    8.5000    8.6618   43.8181   88.7994    2.3584    0.1149   78.9872   -4.0015   49.0000 
+2671.0250    8.5000    8.6699   43.7873   88.6637    2.3577    0.1140   79.0490   -4.0451   49.0000 
+2671.1250    8.5000    8.6454   45.0012   86.0559    2.3647    0.1145   79.0010   -3.8899   49.0000 
+2671.2250    8.5000    8.6045   46.4609   82.9518    2.3728    0.1152   78.8954   -3.7029   49.0000 
+2671.3250    8.5000    8.5963   50.1102   79.7053    2.3792    0.1155   78.6403   -3.5668   49.0000 
+2671.4250    8.5000    8.5963   53.1371   75.8244    2.3798    0.1134   78.2704   -3.6245   49.0000 
+2671.5250    8.5000    8.6045   55.9029   71.7275    2.3831    0.1100   77.8224   -3.6705   49.0000 
+2671.6250    8.5000    8.6127   57.5163   68.5143    2.3887    0.1062   77.2219   -3.6855   49.0000 
+2671.7250    8.5000    8.5963   56.4522   67.0115    2.4064    0.1040   76.5056   -3.4042   49.0000 
+2671.8250    8.5000    8.5963   55.1308   66.9535    2.4296    0.1027   75.7536   -2.9844   49.0000 
+2671.9250    8.5000    8.5963   53.1794   67.2333    2.4575    0.1022   75.2888   -2.4436   49.0000 
+2672.0250    8.5000    8.5800   51.7811   67.3788    2.4730    0.1032   75.3408   -2.0998   49.0000 
+2672.1250    8.5000    8.5800   50.7978   67.5807    2.4657    0.1059   75.9046   -2.1579   49.0000 
+2672.2250    8.5000    8.5800   49.3842   68.4457    2.4379    0.1097   76.8495   -2.5871   49.0000 
+2672.3250    8.5000    8.6127   47.2176   70.9067    2.4005    0.1128   77.8403   -3.2307   49.0000 
+2672.4250    8.5000    8.6454   43.9756   74.8423    2.3692    0.1144   78.6434   -3.8018   49.0000 
+2672.5250    8.5000    8.6536   40.8334   80.6472    2.3434    0.1140   79.1301   -4.3311   49.0000 
+2672.6250    8.5000    8.6699   38.4825   86.7200    2.3275    0.1119   79.2179   -4.7200   49.0000 
+2672.7250    8.5000    8.6618   37.7757   91.7210    2.3237    0.1101   79.0561   -4.8536   49.0000 
+2672.8250    8.5000    8.6536   37.8678   94.1672    2.3344    0.1103   78.8653   -4.6339   49.0000 
+2672.9250    8.5000    8.6618   38.8359   94.0856    2.3526    0.1123   78.7837   -4.2049   49.0000 
+2673.0250    8.5000    8.6209   40.4646   93.3343    2.3648    0.1145   78.9000   -3.8857   49.0000 
+2673.1250    8.5000    8.6045   41.6477   91.9990    2.3693    0.1149   79.0245   -3.7839   49.0000 
+2673.2250    8.5000    8.5963   43.9602   91.2877    2.3662    0.1151   79.1128   -3.8403   49.0000 
+2673.3250    8.5000    8.6290   46.8412   89.2014    2.3638    0.1141   79.0954   -3.9208   49.0000 
+2673.4250    8.5000    8.6454   48.9770   84.7425    2.3607    0.1147   78.8934   -3.9630   49.0000 
+2673.5250    8.5000    8.6454   52.0961   78.8326    2.3604    0.1145   78.5617   -3.9755   49.0000 
+2673.6250    8.5000    8.6945   55.1999   74.8308    2.3629    0.1151   78.0964   -3.9068   49.0000 
+2673.7250    8.5000    8.6618   58.4574   75.7697    2.3669    0.1147   77.6444   -3.8410   49.0000 
+2673.8250    8.5000    8.6618   62.4216   73.2530    2.3712    0.1136   77.2944   -3.7909   49.0000 
+2673.9250    8.5000    8.6699   64.8340   67.2245    2.3712    0.1126   77.0980   -3.8230   49.0000 
+2674.0250    8.5000    8.6536   65.8904   61.4094    2.3724    0.1111   77.0291   -3.8497   49.0000 
+2674.1250    8.5000    8.6372   64.0465   62.4657    2.3751    0.1105   77.0658   -3.8136   49.0000 
+2674.2250    8.5000    8.6209   59.5598   70.3608    2.3811    0.1085   77.1097   -3.7627   49.0000 
+2674.3250    8.5000    8.5963   54.9733   78.8913    2.3865    0.1076   77.1454   -3.6827   49.0000 
+2674.4250    8.5000    8.5800   50.6326   82.9770    2.3865    0.1072   77.1423   -3.6970   49.0000 
+2674.5250    8.5000    8.5963   48.4046   82.3523    2.3836    0.1093   77.1985   -3.6843   49.0000 
+2674.6250    8.5000    8.6290   48.8963   81.3707    2.3802    0.1108   77.3444   -3.7022   49.0000 
+2674.7250    8.5000    8.6699   49.9872   80.8536    2.3803    0.1116   77.5617   -3.6731   49.0000 
+2674.8250    8.5000    8.6945   51.1896   80.0402    2.3807    0.1105   77.7158   -3.7011   49.0000 
+2674.9250    8.5000    8.6945   51.9118   78.4307    2.3785    0.1088   77.6985   -3.8044   49.0000 
+2675.0250    8.5000    8.6699   51.0820   77.2631    2.3766    0.1067   77.4975   -3.9115   49.0000 
+2675.1250    8.5000    8.6454   49.9834   77.1898    2.3801    0.1047   77.1352   -3.9097   49.0000 
+2675.2250    8.5000    8.5800   48.8925   78.0163    2.3842    0.1032   76.7668   -3.8756   49.0000 
+2675.3250    8.5000    8.5963   48.3086   78.5275    2.3845    0.1022   76.4230   -3.9051   49.0000 
+2675.4250    8.5000    8.6290   48.5698   78.6910    2.3785    0.1024   76.1837   -4.0171   49.0000 
+2675.5250    8.5000    8.6127   49.5839   78.8434    2.3768    0.1040   76.0612   -3.9974   49.0000 
+2675.6250    8.5000    8.6372   51.1204   78.6282    2.3813    0.1068   76.0546   -3.8131   49.0000 
+2675.7250    8.5000    8.6290   51.7427   76.7563    2.3874    0.1106   76.1760   -3.5651   49.0000 
+2675.8250    8.5000    8.6209   52.1346   72.2798    2.3944    0.1150   76.4056   -3.2794   49.0000 
+2675.9250    8.5000    8.6209   51.1665   66.8261    2.3962    0.1200   76.7597   -3.0766   49.0000 
+2676.0250    8.5000    8.5800   48.8464   62.2891    2.3948    0.1235   77.1219   -2.9885   49.0000 
+2676.1250    8.5000    8.5881   46.8489   60.0351    2.3848    0.1244   77.4821   -3.1563   49.0000 
+2676.2250    8.5000    8.5636   44.3136   60.2955    2.3741    0.1230   77.7179   -3.4177   49.0000 
+2676.3250    8.5000    8.5554   42.7002   62.3164    2.3646    0.1206   77.8490   -3.6864   49.0000 
+2676.4250    8.5000    8.5718   42.0703   63.7333    2.3606    0.1183   77.9000   -3.8463   49.0000 
+2676.5250    8.5000    8.5636   42.0165   62.9255    2.3616    0.1157   77.8725   -3.9120   49.0000 
+2676.6250    8.5000    8.5800   43.3456   60.8304    2.3665    0.1145   77.7714   -3.8549   49.0000 
+2676.7250    8.5000    8.5963   45.0358   60.2130    2.3695    0.1152   77.5969   -3.7698   49.0000 
+2676.8250    8.5000    8.5800   46.7106   61.4673    2.3689    0.1175   77.3582   -3.7069   49.0000 
+2676.9250    8.5000    8.6127   48.2164   63.7633    2.3693    0.1200   77.1653   -3.6122   49.0000 
+2677.0250    8.5000    8.6209   49.2996   64.8585    2.3747    0.1210   77.0459   -3.4719   49.0000 
+2677.1250    8.5000    8.6781   50.0833   63.9339    2.3806    0.1215   77.0041   -3.3376   49.0000 
+2677.2250    8.5000    8.6863   52.0193   61.7371    2.3875    0.1211   77.0628   -3.2132   49.0000 
+2677.3250    8.5000    8.6699   53.7863   59.0634    2.3918    0.1209   77.2556   -3.1328   49.0000 
+2677.4250    8.5000    8.6536   54.2934   56.3618    2.3973    0.1213   77.7005   -3.0112   49.0000 
+2677.5250    8.5000    8.6290   53.9707   53.7515    2.3931    0.1216   78.4036   -3.0840   49.0000 
+2677.6250    8.5000    8.6127   51.4508   51.9103    2.3884    0.1220   79.2893   -3.1657   49.0000 
+2677.7250    8.5000    8.6290   48.5928   50.9867    2.3805    0.1208   80.0270   -3.3623   49.0000 
+2677.8250    8.5000    8.6699   46.6030   50.8613    2.3805    0.1198   80.4321   -3.3970   49.0000 
+2677.9250    8.5000    8.6618   45.5121   50.7026    2.3767    0.1192   80.3398   -3.4914   49.0000 
+2678.0250    8.5000    8.6372   45.6658   50.1511    2.3753    0.1202   79.7347   -3.4849   49.0000 
+2678.1250    8.5000    8.6290   46.8489   49.4402    2.3678    0.1224   78.9122   -3.5642   49.0000 
+2678.2250    8.5000    8.6454   47.7401   49.1288    2.3652    0.1241   78.0668   -3.5592   49.0000 
+2678.3250    8.5000    8.6618   48.1396   49.5464    2.3652    0.1245   77.6087   -3.5451   49.0000 
+2678.4250    8.5000    8.6781   48.6389   50.6202    2.3737    0.1233   77.4934   -3.4155   49.0000 
+2678.5250    8.5000    8.6945   48.1626   51.9395    2.3804    0.1219   77.6474   -3.3309   49.0000 
+2678.6250    8.5000    8.6699   48.3931   53.0844    2.3838    0.1209   77.8311   -3.2960   49.0000 
+2678.7250    8.5000    8.6209   49.4072   53.9646    2.3802    0.1197   77.9602   -3.4056   49.0000 
+2678.8250    8.5000    8.6290   49.1767   54.8640    2.3771    0.1184   78.0510   -3.5106   49.0000 
+2678.9250    8.5000    8.6045   49.1844   55.8383    2.3771    0.1165   78.2087   -3.5740   49.0000 
+2679.0250    8.5000    8.6372   49.1229   56.8965    2.3826    0.1154   78.4546   -3.5017   49.0000 
+2679.1250    8.5000    8.6372   48.1626   57.8735    2.3867    0.1152   78.6107   -3.4268   49.0000 
+2679.2250    8.5000    8.6372   48.6927   59.0552    2.3842    0.1160   78.6832   -3.4512   49.0000 
+2679.3250    8.5000    8.6209   49.1537   60.7790    2.3737    0.1169   78.4770   -3.6295   49.0000 
+2679.4250    8.5000    8.6045   49.6300   62.7851    2.3614    0.1166   78.2194   -3.8857   49.0000 
+2679.5250    8.5000    8.5881   51.5584   64.3133    2.3554    0.1147   78.0143   -4.0685   49.0000 
+2679.6250    8.5000    8.5881   53.3023   63.5217    2.3572    0.1131   77.9240   -4.0862   49.0000 
+2679.7250    8.5000    8.5963   56.0450   61.0684    2.3647    0.1122   77.9806   -3.9651   49.0000 
+2679.8250    8.5000    8.6209   58.2807   57.9287    2.3727    0.1130   77.9714   -3.7794   49.0000 
+2679.9250    8.5000    8.6209   59.5637   55.8744    2.3806    0.1128   77.9189   -3.6268   49.0000 
+2680.0250    8.5000    8.6290   60.1322   55.2173    2.3899    0.1137   77.8566   -3.4127   49.0000 
+2680.1250    8.5000    8.6372   59.6559   55.9204    2.3949    0.1137   77.8046   -3.3122   49.0000 
+2680.2250    8.5000    8.6372   59.6098   57.1735    2.3922    0.1142   77.8087   -3.3475   49.0000 
+2680.3250    8.5000    8.6290   58.8492   58.0652    2.3797    0.1128   77.7102   -3.6459   49.0000 
+2680.4250    8.5000    8.6290   58.4267   57.9659    2.3697    0.1117   77.4821   -3.8807   49.0000 
+2680.5250    8.5000    8.6209   57.1974   57.1077    2.3647    0.1117   77.2423   -3.9844   49.0000 
+2680.6250    8.5000    8.6209   55.2691   56.1238    2.3672    0.1123   77.0357   -3.9144   49.0000 
+2680.7250    8.5000    8.6536   53.7633   55.2478    2.3714    0.1113   76.8898   -3.8630   49.0000 
+2680.8250    8.5000    8.6372   52.1192   54.6383    2.3762    0.1075   76.7102   -3.8932   49.0000 
+2680.9250    8.5000    8.6699   51.8657   54.6143    2.3809    0.1036   76.4556   -3.9292   49.0000 
+2681.0250    8.5000    8.6781   51.8196   55.0447    2.3807    0.1022   76.2270   -3.9796   49.0000 
+2681.1250    8.5000    8.6536   51.8042   55.3646    2.3788    0.1044   76.2699   -3.9429   49.0000 
+2681.2250    8.5000    8.6699   52.2344   54.5601    2.3760    0.1088   76.6087   -3.8537   49.0000 
+2681.3250    8.5000    8.6454   52.2191   52.3769    2.3783    0.1142   77.1332   -3.6270   49.0000 
+2681.4250    8.5000    8.6290   52.3266   49.2350    2.3827    0.1190   77.6388   -3.3788   49.0000 
+2681.5250    8.5000    8.6209   53.6019   45.6492    2.3885    0.1228   77.8531   -3.1375   49.0000 
+2681.6250    8.5000    8.6290   55.2614   42.1766    2.3977    0.1239   77.9270   -2.9177   49.0000 
+2681.7250    8.5000    8.6290   57.8351   38.7733    2.4131    0.1234   77.8087   -2.6241   49.0000 
+2681.8250    8.5000    8.6209   60.8621   35.5979    2.4303    0.1223   77.5500   -2.3192   49.0000 
+2681.9250    8.5000    8.6209   62.0298   32.8150    2.4402    0.1213   77.2469   -2.1530   49.0000 
+2682.0250    8.5000    8.6290   61.3691   30.8294    2.4429    0.1205   76.8980   -2.1255   49.0000 
+2682.1250    8.5000    8.6290   58.6494   29.7947    2.4367    0.1188   76.6454   -2.3061   49.0000 
+2682.2250    8.5000    8.6209   55.1538   29.6305    2.4297    0.1180   76.4158   -2.4726   49.0000 
+2682.3250    8.5000    8.6372   52.3727   30.0998    2.4187    0.1176   76.1423   -2.7068   49.0000 
+2682.4250    8.5000    8.6618   50.8515   31.0124    2.4117    0.1183   75.8403   -2.8219   49.0000 
+2682.5250    8.5000    8.6536   51.1589   32.2823    2.4064    0.1188   75.7082   -2.9115   49.0000 
+2682.6250    8.5000    8.6699   52.8644   33.9325    2.4034    0.1189   75.8388   -2.9679   49.0000 
+2682.7250    8.5000    8.6618   54.7543   35.7962    2.4077    0.1186   76.1296   -2.8937   49.0000 
+2682.8250    8.5000    8.6209   56.1180   37.5609    2.4155    0.1177   76.4194   -2.7652   49.0000 
+2682.9250    8.5000    8.6536   56.5790   38.9958    2.4252    0.1166   76.4923   -2.6096   49.0000 
+2683.0250    8.5000    8.6454   55.5572   40.2065    2.4249    0.1162   76.2240   -2.6271   49.0000 
+2683.1250    8.5000    8.6045   54.5123   41.4891    2.4172    0.1163   75.6138   -2.7775   49.0000 
+2683.2250    8.5000    8.5881   53.8439   42.7606    2.4061    0.1181   75.0291   -2.9407   49.0000 
+2683.3250    8.5000    8.5963   53.2216   43.6638    2.3992    0.1187   74.7934   -3.0597   49.0000 
+2683.4250    8.5000    8.6045   52.3151   44.0899    2.3991    0.1178   75.2219   -3.0924   49.0000 
+2683.5250    8.5000    8.6209   50.9168   44.2505    2.4066    0.1158   76.0311   -3.0074   49.0000 
+2683.6250    8.5000    8.6618   49.7913   44.4389    2.4153    0.1146   76.6571   -2.8758   49.0000 
+2683.7250    8.5000    8.6290   49.0231   44.2349    2.4226    0.1153   76.8551   -2.7065   49.0000 
+2683.8250    8.5000    8.6209   49.2843   43.1401    2.4241    0.1150   76.4648   -2.6840   49.0000 
+2683.9250    8.5000    8.6209   50.9591   41.0747    2.4277    0.1146   76.0770   -2.6248   49.0000 
+2684.0250    8.5000    8.6127   53.5251   38.2925    2.4372    0.1132   75.8219   -2.4842   49.0000 
+2684.1250    8.5000    8.6209   57.5739   35.1125    2.4533    0.1144   75.7791   -2.1218   49.0000 
+2684.2250    8.5000    8.6127   62.4908   31.9833    2.4644    0.1179   75.8750   -1.7830   49.0000 
+2684.3250    8.5000    8.6127   65.4256   29.5234    2.4692    0.1250   75.8332   -1.4500   49.0000 
+2684.4250    8.5000    8.6045   66.0402   28.2490    2.4674    0.1328   75.9000   -1.2251   49.0000 
+2684.5250    8.5000    8.5881   62.7443   28.2886    2.4617    0.1395   75.9883   -1.1173   49.0000 
+2684.6250    8.5000    8.6045   57.0591   29.5745    2.4442    0.1421   76.1515   -1.3800   49.0000 
+2684.7250    8.5000    8.5718   52.3881   31.9550    2.4189    0.1408   76.2842   -1.9297   49.0000 
+2684.8250    8.5000    8.5800   47.7631   35.2848    2.3941    0.1363   76.3372   -2.5759   49.0000 
+2684.9250    8.5000    8.5800   45.5966   39.4141    2.3739    0.1310   76.3765   -3.1564   49.0000 
+2685.0250    8.5000    8.5718   44.6440   44.0806    2.3550    0.1271   76.6439   -3.6621   49.0000 
+2685.1250    8.5000    8.5636   43.4147   48.7496    2.3376    0.1260   77.2515   -4.0488   49.0000 
+2685.2250    8.5000    8.5800   43.9832   52.8919    2.3273    0.1268   78.0648   -4.2266   49.0000 
+2685.3250    8.5000    8.5881   44.5594   56.0337    2.3264    0.1273   78.8775   -4.2288   49.0000 
+2685.4250    8.5000    8.5963   45.2048   58.1628    2.3279    0.1279   79.3837   -4.1778   49.0000 
+2685.5250    8.5000    8.5963   45.9116   59.1563    2.3283    0.1281   79.6796   -4.1650   49.0000 
+2685.6250    8.5000    8.5963   45.6350   59.4648    2.3240    0.1284   79.8005   -4.2391   49.0000 
+2685.7250    8.5000    8.6045   44.4212   59.4634    2.3192    0.1272   80.0046   -4.3754   49.0000 
+2685.8250    8.5000    8.6290   43.1996   60.1758    2.3130    0.1257   79.9837   -4.5499   49.0000 
+2685.9250    8.5000    8.6290   42.0626   61.4173    2.3109    0.1242   79.7622   -4.6419   49.0000 
+2686.0250    8.5000    8.6127   41.4172   62.8561    2.3091    0.1235   79.5128   -4.7018   49.0000 
+2686.1250    8.5000    8.6127   41.9781   63.6117    2.3114    0.1239   79.4770   -4.6417   49.0000 
+2686.2250    8.5000    8.6045   41.9473   63.5705    2.3129    0.1259   80.0189   -4.5474   49.0000 
+2686.3250    8.5000    8.6045   42.6080   62.8158    2.3182    0.1295   80.9362   -4.3190   49.0000 
+2686.4250    8.5000    8.5963   43.3456   61.4670    2.3234    0.1329   82.0423   -4.1013   49.0000 
+2686.5250    8.5000    8.5636   43.9986   59.9891    2.3319    0.1352   83.0071   -3.8569   49.0000 
+2686.6250    8.5000    8.5391   46.2496   58.8675    2.3414    0.1356   83.5735   -3.6542   49.0000 
+2686.7250    8.5000    8.5472   48.9232   58.4000    2.3499    0.1345   83.5939   -3.5181   49.0000 
+2686.8250    8.5000    8.5472   52.4342   57.7393    2.3548    0.1322   82.9577   -3.4989   49.0000 
+2686.9250    8.5000    8.5554   57.0515   55.5058    2.3576    0.1280   81.8597   -3.5814   49.0000 
+2687.0250    8.5000    8.5718   60.4779   51.3202    2.3659    0.1242   80.5862   -3.5428   49.0000 
+2687.1250    8.5000    8.5800   62.1374   46.2885    2.3832    0.1217   79.4097   -3.2799   49.0000 
+2687.2250    8.5000    8.5963   61.3537   42.3808    2.4053    0.1209   78.4622   -2.8636   49.0000 
+2687.3250    8.5000    8.6045   57.6891   40.5942    2.4242    0.1190   77.7005   -2.5484   49.0000 
+2687.4250    8.5000    8.5963   53.3484   41.5894    2.4310    0.1143   77.0342   -2.5684   49.0000 
+2687.5250    8.5000    8.5800   48.8925   45.3896    2.4274    0.1083   76.2617   -2.8440   49.0000 
+2687.6250    8.5000    8.5800   45.7042   52.0542    2.4173    0.1025   75.3434   -3.2374   49.0000 
+2687.7250    8.5000    8.5800   43.5530   60.9338    2.4073    0.0988   74.2587   -3.5605   49.0000 
+2687.8250    8.5000    8.5718   42.2777   70.9879    2.3987    0.0964   73.2250   -3.8134   49.0000 
+2687.9250    8.5000    8.5554   41.8936   80.3410    2.3926    0.0962   72.7214   -3.9417   49.0000 
+2688.0250    8.5000    8.5472   40.8794   86.7924    2.3874    0.0980   72.9138   -3.9833   49.0000 
+2688.1250    8.5000    8.5391   39.2815   88.6920    2.3841    0.1017   73.7423   -3.9266   49.0000 
+2688.2250    8.5000    8.5472   37.8755   86.7090    2.3759    0.1058   74.9898   -3.9549   49.0000 
+2688.3250    8.5000    8.5554   36.3236   81.6682    2.3676    0.1096   76.4112   -3.9942   49.0000 
+2688.4250    8.5000    8.5554   37.1226   74.0237    2.3593    0.1138   77.6194   -4.0188   49.0000 
+2688.5250    8.5000    8.5636   41.8244   64.9579    2.3606    0.1175   78.3694   -3.8693   49.0000 
+2688.6250    8.5000    8.5554   48.8771   55.5810    2.3682    0.1204   78.6092   -3.6216   49.0000 
+2688.7250    8.5000    8.5800   58.1117   46.9570    2.3873    0.1212   78.5806   -3.2136   49.0000 
+2688.8250    8.5000    8.5881   64.8033   39.8464    2.4131    0.1235   78.7765   -2.6220   49.0000 
+2688.9250    8.5000    8.5718   66.9544   34.7661    2.4398    0.1277   79.1138   -1.9487   49.0000 
+2689.0250    8.5000    8.5963   64.5267   31.9041    2.4457    0.1326   79.2556   -1.6676   49.0000 
+2689.1250    8.5000    8.5718   58.4343   31.2962    2.4298    0.1321   79.0679   -2.0005   49.0000 
+2689.2250    8.5000    8.5963   53.0872   32.9740    2.4001    0.1264   78.7204   -2.7864   49.0000 
+2689.3250    8.5000    8.6127   49.0538   36.8079    2.3804    0.1188   78.6357   -3.4317   49.0000 
+2689.4250    8.5000    8.5881   47.3483   42.3432    2.3708    0.1158   78.9765   -3.7258   49.0000 
+2689.5250    8.5000    8.5718   47.6402   48.5146    2.3694    0.1175   79.4000   -3.6947   49.0000 
+2689.6250    8.5000    8.5636   48.5544   53.9279    2.3669    0.1223   79.6291   -3.5859   49.0000 
+2689.7250    8.5000    8.5718   49.5148   57.6889    2.3631    0.1256   79.6913   -3.5513   49.0000 
+2689.8250    8.5000    8.5881   49.6838   59.7665    2.3573    0.1264   79.6464   -3.6390   49.0000 
+2689.9250    8.5000    8.5800   48.6313   61.2940    2.3534    0.1241   79.6225   -3.7953   49.0000 
+2690.0250    8.5000    8.5800   46.0806   63.2667    2.3541    0.1211   79.4357   -3.8823   49.0000 
+2690.1250    8.5000    8.5718   43.2764   66.5642    2.3573    0.1183   79.2306   -3.9096   49.0000 
+2690.2250    8.5000    8.5881   40.4800   69.9570    2.3583    0.1159   79.1296   -3.9706   49.0000 
+2690.3250    8.5000    8.5963   38.7667   72.6449    2.3568    0.1131   79.2969   -4.0938   49.0000 
+2690.4250    8.5000    8.5963   38.4440   73.9109    2.3535    0.1111   79.5816   -4.2242   49.0000 
+2690.5250    8.5000    8.5636   38.9742   75.2450    2.3507    0.1113   79.8031   -4.2743   49.0000 
+2690.6250    8.5000    8.5472   39.9038   77.7118    2.3478    0.1132   79.8026   -4.2698   49.0000 
+2690.7250    8.5000    8.5554   40.6106   81.3753    2.3501    0.1148   79.5434   -4.1694   49.0000 
+2690.8250    8.5000    8.5718   40.6874   85.5841    2.3551    0.1156   79.1209   -4.0440   49.0000 
+2690.9250    8.5000    8.5963   40.8794   88.7932    2.3604    0.1155   78.5934   -3.9412   49.0000 
+2691.0250    8.5000    8.5963   41.9397   90.4645    2.3590    0.1144   78.2026   -4.0058   49.0000 
+2691.1250    8.5000    8.5718   43.4147   89.5335    2.3512    0.1131   77.9832   -4.2053   49.0000 
+2691.2250    8.5000    8.6045   45.5198   86.3202    2.3410    0.1126   77.9352   -4.4250   49.0000 
+2691.3250    8.5000    8.6045   46.5339   81.1140    2.3333    0.1137   77.9602   -4.5434   49.0000 
+2691.4250    8.5000    8.5881   46.7797   75.7315    2.3335    0.1146   77.9954   -4.5097   49.0000 
+2691.5250    8.5000    8.5963   46.6875   71.3634    2.3421    0.1149   78.0913   -4.3294   49.0000 
+2691.6250    8.5000    8.5800   46.8412   68.3625    2.3590    0.1148   78.2510   -3.9916   49.0000 
+2691.7250    8.5000    8.5800   47.5557   66.4688    2.3773    0.1150   78.4469   -3.6199   49.0000 
+2691.8250    8.5000    8.5800   48.7695   65.1401    2.3874    0.1163   78.5556   -3.3764   49.0000 
+2691.9250    8.5000    8.5636   49.6223   63.9819    2.3832    0.1178   78.5770   -3.4095   49.0000 
+2692.0250    8.5000    8.5472   49.3304   63.0079    2.3734    0.1207   78.5383   -3.5068   49.0000 
+2692.1250    8.5000    8.5309   49.8528   61.8356    2.3663    0.1228   78.5541   -3.5819   49.0000 
+2692.2250    8.5000    8.5472   49.0000   60.4625    2.3700    0.1236   78.6337   -3.4807   49.0000 
+2692.3250    8.5000    8.5472   48.0935   59.0667    2.3749    0.1227   78.7607   -3.4129   49.0000 
+2692.4250    8.5000    8.5881   47.9706   58.4272    2.3797    0.1218   78.9474   -3.3457   49.0000 
+2692.5250    8.5000    8.5963   46.6261   58.7753    2.3788    0.1220   79.1714   -3.3555   49.0000 
+2692.6250    8.5000    8.5800   46.1574   60.1926    2.3749    0.1234   79.4755   -3.3887   49.0000 
+2692.7250    8.5000    8.5800   46.7336   61.6657    2.3707    0.1250   79.7133   -3.4200   49.0000 
+2692.8250    8.5000    8.5718   47.3636   62.9756    2.3653    0.1250   79.8725   -3.5289   49.0000 
+2692.9250    8.5000    8.5718   48.1933   63.9891    2.3621    0.1230   79.9653   -3.6585   49.0000 
+2693.0250    8.5000    8.5800   48.9155   65.6913    2.3559    0.1194   80.1005   -3.9010   49.0000 
+2693.1250    8.5000    8.6045   48.0858   68.9459    2.3543    0.1173   80.2658   -4.0037   49.0000 
+2693.2250    8.5000    8.6127   46.5646   73.9325    2.3525    0.1168   80.4046   -4.0575   49.0000 
+2693.3250    8.5000    8.6127   45.8040   79.8370    2.3551    0.1186   80.4020   -3.9439   49.0000 
+2693.4250    8.5000    8.6127   45.3661   84.1890    2.3532    0.1207   80.2633   -3.9115   49.0000 
+2693.5250    8.5000    8.5881   46.1498   86.1717    2.3565    0.1219   80.1393   -3.8076   49.0000 
+2693.6250    8.5000    8.5881   46.8412   86.0329    2.3597    0.1207   80.2077   -3.7816   49.0000 
+2693.7250    8.5000    8.5718   46.5493   85.8588    2.3691    0.1169   80.3622   -3.7216   49.0000 
+2693.8250    8.5000    8.5718   45.5812   86.4317    2.3754    0.1128   80.4776   -3.7308   49.0000 
+2693.9250    8.5000    8.5718   44.7054   87.4784    2.3796    0.1095   80.2582   -3.7595   49.0000 
+2694.0250    8.5000    8.5636   44.6593   88.0846    2.3808    0.1081   79.6474   -3.7793   49.0000 
+2694.1250    8.5000    8.5963   44.8437   87.8386    2.3740    0.1081   79.0066   -3.9160   49.0000 
+2694.2250    8.5000    8.6127   45.8809   86.9920    2.3686    0.1094   78.4255   -3.9829   49.0000 
+2694.3250    8.5000    8.6209   46.1959   85.2841    2.3615    0.1109   78.1429   -4.0731   49.0000 
+2694.4250    8.5000    8.6045   45.6120   82.8935    2.3667    0.1117   78.0260   -3.9417   49.0000 
+2694.5250    8.5000    8.5963   45.4276   80.5847    2.3714    0.1113   77.9740   -3.8605   49.0000 
+2694.6250    8.5000    8.5881   44.9666   78.8961    2.3779    0.1108   77.8250   -3.7485   49.0000 
+2694.7250    8.5000    8.5718   45.3969   77.9349    2.3768    0.1107   77.5311   -3.7744   49.0000 
+2694.8250    8.5000    8.5963   46.5032   77.2282    2.3771    0.1114   77.1291   -3.7457   49.0000 
+2694.9250    8.5000    8.6045   47.2100   77.1541    2.3766    0.1114   76.6964   -3.7559   49.0000 
+2695.0250    8.5000    8.6290   48.7695   77.0424    2.3798    0.1117   76.4168   -3.6818   49.0000 
+2695.1250    8.5000    8.6454   49.2228   76.4384    2.3803    0.1114   76.2041   -3.6814   49.0000 
+2695.2250    8.5000    8.6209   50.0679   74.7241    2.3799    0.1115   76.1225   -3.6863   49.0000 
+2695.3250    8.5000    8.6209   51.3125   72.6423    2.3754    0.1107   76.1020   -3.8024   49.0000 
+2695.4250    8.5000    8.6045   50.2062   70.6842    2.3723    0.1105   76.0954   -3.8722   49.0000 
+2695.5250    8.5000    8.5963   48.3931   69.0924    2.3695    0.1113   76.0964   -3.8986   49.0000 
+2695.6250    8.5000    8.5881   45.2586   67.7560    2.3650    0.1128   75.9413   -3.9399   49.0000 
+2695.7250    8.5000    8.5718   41.9858   67.5557    2.3550    0.1136   75.6944   -4.1127   49.0000 
+2695.8250    8.5000    8.5718   39.8192   68.6573    2.3455    0.1131   75.4786   -4.3208   49.0000 
+2695.9250    8.5000    8.5636   40.0344   71.0872    2.3443    0.1125   75.5128   -4.3625   49.0000 
+2696.0250    8.5000    8.5800   41.2405   73.1065    2.3532    0.1127   75.8995   -4.1776   49.0000 
+2696.1250    8.5000    8.5554   42.7771   73.9456    2.3620    0.1137   76.6225   -3.9714   49.0000 
+2696.2250    8.5000    8.5554   44.7054   72.8699    2.3616    0.1145   77.4337   -3.9514   49.0000 
+2696.3250    8.5000    8.5554   44.6977   71.1890    2.3524    0.1149   78.1357   -4.1236   49.0000 
+2696.4250    8.5000    8.5636   44.8821   69.6906    2.3444    0.1149   78.5112   -4.2813   49.0000 
+2696.5250    8.5000    8.5800   44.6516   68.5928    2.3455    0.1144   78.4383   -4.2758   49.0000 
+2696.6250    8.5000    8.5881   44.1523   67.9098    2.3534    0.1135   77.9827   -4.1498   49.0000 
+2696.7250    8.5000    8.5800   43.8911   67.3193    2.3620    0.1121   77.3597   -4.0212   49.0000 
+2696.8250    8.5000    8.5718   43.0844   67.2252    2.3691    0.1113   76.8862   -3.9087   49.0000 
+2696.9250    8.5000    8.5718   42.4237   67.1070    2.3762    0.1109   76.6985   -3.7805   49.0000 
+2697.0250    8.5000    8.5963   43.3072   66.7015    2.3827    0.1112   76.6444   -3.6397   49.0000 
+2697.1250    8.5000    8.5963   45.6504   65.6575    2.3894    0.1121   76.5770   -3.4765   49.0000 
+2697.2250    8.5000    8.5881   49.1383   64.3246    2.3911    0.1131   76.3872   -3.4065   49.0000 
+2697.3250    8.5000    8.5636   52.4572   62.9522    2.3878    0.1141   76.2250   -3.4393   49.0000 
+2697.4250    8.5000    8.5391   53.9169   61.2839    2.3793    0.1138   76.1673   -3.6222   49.0000 
+2697.5250    8.5000    8.5554   54.2242   59.0653    2.3781    0.1136   76.2745   -3.6515   49.0000 
+2697.6250    8.5000    8.5800   53.5558   56.1724    2.3846    0.1140   76.4684   -3.5086   49.0000 
+2697.7250    8.5000    8.6209   53.4329   52.8804    2.3979    0.1165   76.7418   -3.1584   49.0000 
+2697.8250    8.5000    8.6290   53.4790   49.7779    2.4021    0.1185   77.1163   -3.0095   49.0000 
+2697.9250    8.5000    8.6454   54.2473   47.5473    2.3998    0.1179   77.5643   -3.0728   49.0000 
+2698.0250    8.5000    8.6290   54.6314   46.7506    2.3862    0.1148   78.1071   -3.4474   49.0000 
+2698.1250    8.5000    8.6127   54.3395   47.9309    2.3735    0.1121   78.5194   -3.7922   49.0000 
+2698.2250    8.5000    8.5963   53.3330   51.5612    2.3613    0.1108   78.7102   -4.0800   49.0000 
+2698.3250    8.5000    8.5800   51.2664   57.7382    2.3539    0.1105   78.6949   -4.2384   49.0000 
+2698.4250    8.5000    8.5800   49.3995   65.1279    2.3472    0.1097   78.5270   -4.3992   49.0000 
+2698.5250    8.5000    8.5881   47.7477   72.4162    2.3422    0.1094   78.3015   -4.5084   49.0000 
+2698.6250    8.5000    8.5800   48.2471   78.4534    2.3431    0.1079   78.0740   -4.5415   49.0000 
+2698.7250    8.5000    8.5718   49.3534   84.0475    2.3517    0.1057   77.7525   -4.4432   49.0000 
+2698.8250    8.5000    8.5881   50.8208   87.3151    2.3628    0.1027   77.4383   -4.3218   49.0000 
+2698.9250    8.5000    8.5881   51.5968   87.4531    2.3732    0.1013   77.1883   -4.1576   49.0000 
+2699.0250    8.5000    8.5881   50.2753   86.1112    2.3787    0.1017   77.0117   -4.0347   49.0000 
+2699.1250    8.5000    8.6045   48.2625   85.6918    2.3814    0.1021   76.9036   -3.9672   49.0000 
+2699.2250    8.5000    8.5881   44.8437   86.5198    2.3829    0.1019   76.8668   -3.9470   49.0000 
+2699.3250    8.5000    8.5881   41.7706   87.4599    2.3849    0.1010   76.8199   -3.9344   49.0000 
+2699.4250    8.5000    8.5800   39.6272   88.0129    2.3880    0.1018   76.7964   -3.8481   49.0000 
+2699.5250    8.5000    8.5718   38.4440   87.3333    2.3847    0.1035   76.7005   -3.8569   49.0000 
+2699.6250    8.5000    8.5718   39.7117   86.0001    2.3762    0.1050   76.4515   -3.9764   49.0000 
+2699.7250    8.5000    8.5800   42.5082   83.2864    2.3674    0.1056   76.2332   -4.1309   49.0000 
+2699.8250    8.5000    8.5718   46.2727   81.2426    2.3662    0.1057   76.0612   -4.1520   49.0000 
+2699.9250    8.5000    8.5718   49.5762   79.9755    2.3708    0.1062   75.9694   -4.0441   49.0000 
+2700.0250    8.5000    8.5636   51.2895   79.9515    2.3783    0.1063   75.8622   -3.8918   49.0000 
+2700.1250    8.5000    8.5636   51.5660   79.7404    2.3797    0.1063   75.7398   -3.8607   49.0000 
+2700.2250    8.5000    8.5800   50.5366   78.7983    2.3777    0.1064   75.6633   -3.9011   49.0000 
+2700.3250    8.5000    8.6045   50.3368   77.0557    2.3665    0.1060   75.8658   -4.1351   49.0000 
+2700.4250    8.5000    8.6045   51.5968   75.0740    2.3594    0.1063   76.3260   -4.2673   49.0000 
+2700.5250    8.5000    8.5800   54.6314   72.5750    2.3581    0.1066   76.9265   -4.2848   49.0000 
+2700.6250    8.5000    8.5636   58.5957   69.3298    2.3678    0.1095   77.3980   -3.9947   49.0000 
+2700.7250    8.5000    8.5554   62.5446   65.8363    2.3827    0.1129   77.5071   -3.5835   49.0000 
+2700.8250    8.5000    8.5800   64.0811   62.7966    2.3957    0.1183   77.2755   -3.1419   49.0000 
+2700.9250    8.5000    8.5963   62.4677   61.3917    2.4059    0.1231   76.7480   -2.7795   49.0000 
+2701.0250    8.5000    8.5800   60.0246   61.2441    2.4106    0.1282   76.2597   -2.5137   49.0000 
+2701.1250    8.5000    8.5718   56.0297   61.5962    2.4106    0.1317   76.0556   -2.3988   49.0000 
+2701.2250    8.5000    8.5800   54.0168   61.4957    2.4055    0.1330   76.2429   -2.4545   49.0000 
+2701.3250    8.5000    8.5881   54.2473   61.3227    2.3957    0.1317   76.7770   -2.6969   49.0000 
+2701.4250    8.5000    8.5963   54.3087   61.3907    2.3856    0.1316   77.2903   -2.9028   49.0000 
+2701.5250    8.5000    8.5800   54.6391   61.3923    2.3771    0.1338   77.6709   -2.9990   49.0000 
+2701.6250    8.5000    8.5718   53.7479   60.7207    2.3724    0.1376   77.8607   -2.9659   49.0000 
+2701.7250    8.5000    8.5718   52.4803   59.5447    2.3711    0.1381   77.9311   -2.9755   49.0000 
+2701.8250    8.5000    8.5800   51.6813   58.4835    2.3700    0.1363   78.0077   -3.0571   49.0000 
+2701.9250    8.5000    8.5963   51.8042   57.0868    2.3697    0.1333   78.1362   -3.1615   49.0000 
+2702.0250    8.5000    8.5800   52.8721   55.3889    2.3705    0.1315   78.2602   -3.2071   49.0000 
+2702.1250    8.5000    8.5718   53.0642   53.5928    2.3708    0.1301   78.4031   -3.2483   49.0000 
+2702.2250    8.5000    8.5636   52.8875   53.2206    2.3686    0.1294   78.4949   -3.3144   49.0000 
+2702.3250    8.5000    8.5718   51.7888   54.6029    2.3590    0.1300   78.5663   -3.4882   49.0000 
+2702.4250    8.5000    8.5800   49.3918   57.0957    2.3529    0.1311   78.7092   -3.5722   49.0000 
+2702.5250    8.5000    8.5718   47.5634   58.2782    2.3486    0.1319   78.8316   -3.6308   49.0000 
+2702.6250    8.5000    8.5718   46.2880   56.9758    2.3493    0.1317   78.8980   -3.6244   49.0000 
+2702.7250    8.5000    8.5718   46.4187   54.3112    2.3464    0.1295   78.8163   -3.7540   49.0000 
+2702.8250    8.5000    8.5881   47.5096   52.7804    2.3448    0.1271   78.6020   -3.8662   49.0000 
+2702.9250    8.5000    8.5881   48.8233   53.0052    2.3481    0.1257   78.3367   -3.8488   49.0000 
+2703.0250    8.5000    8.5881   50.1371   54.8490    2.3581    0.1259   78.1429   -3.6421   49.0000 
+2703.1250    8.5000    8.5881   50.4290   56.6198    2.3694    0.1258   78.0306   -3.4204   49.0000 
+2703.2250    8.5000    8.5881   50.8746   57.2490    2.3739    0.1250   78.0000   -3.3552   49.0000 
+2703.3250    8.5000    8.5800   50.7363   56.1469    2.3685    0.1241   77.9949   -3.4941   49.0000 
+2703.4250    8.5000    8.5718   50.3214   54.2974    2.3597    0.1240   77.9235   -3.6728   49.0000 
+2703.5250    8.5000    8.5718   50.0679   52.5973    2.3553    0.1228   77.7704   -3.7985   49.0000 
+2703.6250    8.5000    8.5636   49.4072   51.3803    2.3580    0.1214   77.5357   -3.7921   49.0000 
+2703.7250    8.5000    8.5718   48.7542   50.4897    2.3622    0.1194   77.3112   -3.7749   49.0000 
+2703.8250    8.5000    8.5718   48.2010   49.9085    2.3628    0.1191   77.2500   -3.7736   49.0000 
+2703.9250    8.5000    8.5718   47.0025   49.7436    2.3641    0.1191   77.3520   -3.7466   49.0000 
+2704.0250    8.5000    8.5800   46.5493   49.8580    2.3667    0.1188   77.5918   -3.7077   49.0000 
+2704.1250    8.5000    8.5881   46.7797   50.0904    2.3711    0.1157   77.6480   -3.7232   49.0000 
+2704.2250    8.5000    8.5881   46.1267   50.2019    2.3775    0.1101   77.4102   -3.7784   49.0000 
+2704.3250    8.5000    8.5800   46.8719   50.4021    2.3888    0.1046   76.9194   -3.7386   49.0000 
+2704.4250    8.5000    8.5800   47.3098   50.8789    2.4043    0.1025   76.3255   -3.4956   49.0000 
+2704.5250    8.5000    8.5718   48.0858   51.8182    2.4126    0.1040   75.9816   -3.2815   49.0000 
+2704.6250    8.5000    8.5800   50.5212   53.0830    2.4107    0.1069   75.8602   -3.2213   49.0000 
+2704.7250    8.5000    8.5718   51.8426   54.6723    2.3964    0.1087   76.0413   -3.4483   49.0000 
+2704.8250    8.5000    8.5800   53.0795   56.2634    2.3834    0.1097   76.4842   -3.6740   49.0000 
+2704.9250    8.5000    8.5800   54.0014   57.4584    2.3768    0.1099   77.0587   -3.8028   49.0000 
+2705.0250    8.5000    8.5718   54.7928   57.4297    2.3805    0.1106   77.5740   -3.7043   49.0000 
+2705.1250    8.5000    8.5963   57.8581   56.2526    2.3852    0.1113   77.7883   -3.5840   49.0000 
+2705.2250    8.5000    8.6045   61.5765   53.9242    2.3891    0.1139   77.6240   -3.4226   49.0000 
+2705.3250    8.5000    8.6045   65.3257   50.5596    2.4011    0.1169   77.3352   -3.0815   49.0000 
+2705.4250    8.5000    8.5963   67.5921   46.4501    2.4186    0.1211   77.1275   -2.5914   49.0000 
+2705.5250    8.5000    8.5636   66.1708   42.6152    2.4306    0.1248   77.1582   -2.2265   49.0000 
+2705.6250    8.5000    8.5554   62.1604   40.2823    2.4205    0.1276   77.4653   -2.3377   49.0000 
+2705.7250    8.5000    8.5391   55.5226   40.3850    2.3955    0.1273   77.9740   -2.8482   49.0000 
+2705.8250    8.5000    8.5636   48.3547   43.3031    2.3699    0.1258   78.4577   -3.4085   49.0000 
+2705.9250    8.5000    8.5636   43.3379   48.7759    2.3563    0.1244   78.7556   -3.7266   49.0000 
+2706.0250    8.5000    8.5881   40.4723   55.9103    2.3527    0.1253   78.7821   -3.7684   49.0000 
+2706.1250    8.5000    8.5881   40.7027   62.8129    2.3572    0.1262   78.6352   -3.6508   49.0000 
+2706.2250    8.5000    8.5800   42.9154   68.4097    2.3614    0.1272   78.5036   -3.5321   49.0000 
+2706.3250    8.5000    8.5881   43.6298   71.7148    2.3673    0.1263   78.4240   -3.4434   49.0000 
+2706.4250    8.5000    8.5881   43.8603   73.8056    2.3696    0.1242   78.3673   -3.4678   49.0000 
+2706.5250    8.5000    8.5963   43.9832   74.9171    2.3744    0.1195   78.3061   -3.5277   49.0000 
+2706.6250    8.5000    8.5881   44.6055   75.5255    2.3789    0.1140   78.2806   -3.6231   49.0000 
+2706.7250    8.5000    8.5881   47.9782   74.8545    2.3873    0.1096   78.3015   -3.5994   49.0000 
+2706.8250    8.5000    8.5800   51.8580   73.2891    2.3875    0.1088   78.3566   -3.6244   49.0000 
+2706.9250    8.5000    8.5881   54.4009   71.4913    2.3858    0.1124   78.4015   -3.5361   49.0000 
+2707.0250    8.5000    8.5963   54.9080   70.3950    2.3741    0.1174   78.3612   -3.6038   49.0000 
+2707.1250    8.5000    8.5963   52.7799   69.4395    2.3672    0.1219   78.4194   -3.5947   49.0000 
+2707.2250    8.5000    8.5881   49.9296   68.4175    2.3553    0.1229   78.6230   -3.7978   49.0000 
+2707.3250    8.5000    8.5800   48.5621   66.9831    2.3508    0.1228   78.8862   -3.8907   49.0000 
+2707.4250    8.5000    8.5800   48.0243   65.3861    2.3479    0.1222   78.9694   -3.9690   49.0000 
+2707.5250    8.5000    8.5800   48.3547   63.0356    2.3528    0.1226   78.5036   -3.8587   49.0000 
+2707.6250    8.5000    8.5881   48.7234   60.3608    2.3576    0.1236   77.6005   -3.7276   49.0000 
+2707.7250    8.5000    8.5800   46.5800   58.6529    2.3620    0.1254   76.5878   -3.5807   49.0000 
+2707.8250    8.5000    8.5881   44.0293   58.7989    2.3643    0.1289   76.0490   -3.4180   49.0000 
+2707.9250    8.5000    8.5636   42.1625   60.9886    2.3632    0.1329   76.4464   -3.3066   49.0000 
+2708.0250    8.5000    8.5718   40.4953   64.1232    2.3557    0.1363   77.5056   -3.3415   49.0000 
+2708.1250    8.5000    8.5963   41.7860   67.3285    2.3432    0.1369   78.9556   -3.5736   49.0000 
+2708.2250    8.5000    8.5881   43.9832   70.0030    2.3329    0.1351   80.0306   -3.8403   49.0000 
+2708.3250    8.5000    8.5881   46.7260   72.2804    2.3301    0.1325   80.3985   -3.9827   49.0000 
+2708.4250    8.5000    8.5800   53.0949   72.5127    2.3369    0.1326   80.1321   -3.8416   49.0000 
+2708.5250    8.5000    8.5800   62.9825   66.7873    2.3523    0.1362   79.5189   -3.4139   49.0000 
+2708.6250    8.5000    8.5800   76.9188   52.2137    2.3810    0.1450   79.1122   -2.5473   49.0000 
+2708.7250    8.5000    8.5963   92.0229   34.9683    2.4250    0.1566   79.2031   -1.2800   49.0000 
+2708.8250    8.5000    8.6045  102.2332   22.8176    2.4732    0.1698   79.7347    0.1225   54.0000 
+2708.9250    8.5000    8.5963  102.8478   16.3950    2.5098    0.1784   80.2816    1.1423   57.0000 
+2709.0250    8.5000    8.5881   94.5352   13.7180    2.5136    0.1787   80.5444    1.2297   57.0000 
+2709.1250    8.5000    8.5881   79.8766   13.4781    2.4884    0.1679   80.1913    0.3653   57.0000 
+2709.2250    8.5000    8.5800   64.4883   15.1930    2.4400    0.1508   79.4107   -1.1735   49.0000 
+2709.3250    8.5000    8.6127   54.0014   18.8260    2.3956    0.1334   78.6296   -2.6413   49.0000 
+2709.4250    8.5000    8.5963   47.2100   24.4269    2.3683    0.1212   77.9903   -3.5932   49.0000 
+2709.5250    8.5000    8.6045   44.6516   32.1704    2.3656    0.1151   77.7923   -3.8507   49.0000 
+2709.6250    8.5000    8.6209   44.5364   42.7215    2.3700    0.1123   77.7750   -3.8580   49.0000 
+2709.7250    8.5000    8.5881   43.9372   57.2135    2.3744    0.1112   77.8832   -3.8055   49.0000 
+2709.8250    8.5000    8.5881   43.7528   76.0622    2.3697    0.1102   78.0301   -3.9307   49.0000 
+2709.9250    8.5000    8.5881   43.1458  100.3576    2.3670    0.1094   78.0423   -4.0120   49.0000 
+2710.0250    8.5000    8.5800   41.3942  130.6429    2.3630    0.1086   77.9526   -4.1194   49.0000 
+2710.1250    8.5000    8.6290   39.5811  166.1411    2.3658    0.1085   77.7255   -4.0676   49.0000 
+2710.2250    8.5000    8.6209   38.8128  199.2516    2.3648    0.1091   77.6929   -4.0672   49.0000 
+2710.3250    8.5000    8.6209   38.3519  216.9001    2.3644    0.1098   77.8847   -4.0527   49.0000 
+2710.4250    8.5000    8.6454   38.9665  215.2831    2.3601    0.1095   78.2367   -4.1494   49.0000 
+2710.5250    8.5000    8.6127   40.1035  199.0392    2.3635    0.1095   78.4592   -4.0781   49.0000 
+2710.6250    8.5000    8.6209   40.4723  178.4657    2.3672    0.1091   78.3561   -4.0177   49.0000 
+2710.7250    8.5000    8.6290   41.1944  158.2631    2.3699    0.1099   78.1270   -3.9407   49.0000 
+2710.8250    8.5000    8.6290   41.4710  143.2992    2.3632    0.1111   77.7546   -4.0340   49.0000 
+2710.9250    8.5000    8.6209   42.4390  129.8544    2.3566    0.1158   77.4638   -4.0090   49.0000 
+2711.0250    8.5000    8.6209   43.2380  116.8214    2.3566    0.1190   77.2311   -3.9030   49.0000 
+2711.1250    8.5000    8.6045   44.1676  104.2717    2.3618    0.1197   77.1923   -3.7721   49.0000 
+2711.2250    8.5000    8.5718   45.7042   94.7779    2.3666    0.1160   77.4107   -3.8016   49.0000 
+2711.3250    8.5000    8.5718   46.0345   88.8244    2.3658    0.1125   77.6566   -3.9335   49.0000 
+2711.4250    8.5000    8.5718   46.8873   85.2229    2.3672    0.1097   77.8816   -4.0001   49.0000 
+2711.5250    8.5000    8.5636   48.3931   81.9626    2.3686    0.1076   77.9663   -4.0398   49.0000 
+2711.6250    8.5000    8.5718   50.3214   78.4715    2.3708    0.1072   77.9857   -4.0092   49.0000 
+2711.7250    8.5000    8.6045   52.7953   74.3264    2.3702    0.1082   77.9939   -3.9884   49.0000 
+2711.8250    8.5000    8.5963   55.2383   70.7939    2.3729    0.1107   77.9582   -3.8506   49.0000 
+2711.9250    8.5000    8.6045   55.2691   67.6602    2.3764    0.1128   77.8327   -3.7098   49.0000 
+2712.0250    8.5000    8.5881   53.8785   65.6530    2.3842    0.1153   77.6184   -3.4731   49.0000 
+2712.1250    8.5000    8.5963   52.1499   64.4797    2.3926    0.1177   77.3367   -3.2230   49.0000 
+2712.2250    8.5000    8.6290   49.4149   63.9115    2.4036    0.1206   77.1041   -2.9094   49.0000 
+2712.3250    8.5000    8.6618   47.0563   63.1286    2.4095    0.1237   76.9449   -2.6878   49.0000 
+2712.4250    8.5000    8.6127   44.3597   61.9714    2.4077    0.1263   76.8265   -2.6361   49.0000 
+2712.5250    8.5000    8.6209   41.9858   60.9882    2.3998    0.1277   76.8133   -2.7480   49.0000 
+2712.6250    8.5000    8.5963   40.5952   60.7605    2.3897    0.1274   76.8847   -2.9587   49.0000 
+2712.7250    8.5000    8.5963   40.6951   60.7338    2.3807    0.1266   77.1311   -3.1665   49.0000 
+2712.8250    8.5000    8.6127   42.1317   60.1639    2.3723    0.1251   77.4668   -3.3841   49.0000 
+2712.9250    8.5000    8.6209   43.9141   58.8379    2.3647    0.1237   77.7393   -3.5819   49.0000 
+2713.0250    8.5000    8.6127   45.2739   58.0228    2.3582    0.1237   77.8719   -3.7141   49.0000 
+2713.1250    8.5000    8.5881   45.5582   58.3428    2.3556    0.1249   77.7781   -3.7236   49.0000 
+2713.2250    8.5000    8.5881   45.2125   59.2267    2.3586    0.1266   77.4872   -3.6088   49.0000 
+2713.3250    8.5000    8.5881   44.2598   59.8612    2.3678    0.1264   77.0556   -3.4300   49.0000 
+2713.4250    8.5000    8.5963   43.5453   60.1376    2.3722    0.1258   76.6582   -3.3605   49.0000 
+2713.5250    8.5000    8.6045   44.0601   60.7103    2.3719    0.1248   76.4439   -3.4027   49.0000 
+2713.6250    8.5000    8.6209   45.2355   61.7056    2.3650    0.1245   76.4898   -3.5492   49.0000 
+2713.7250    8.5000    8.6209   46.5723   63.0567    2.3603    0.1243   76.7449   -3.6505   49.0000 
+2713.8250    8.5000    8.6045   48.2471   65.0116    2.3547    0.1241   76.9439   -3.7686   49.0000 
+2713.9250    8.5000    8.5800   49.6070   67.8155    2.3519    0.1240   76.9847   -3.8281   49.0000 
+2714.0250    8.5000    8.5800   50.4060   71.2135    2.3510    0.1237   76.7551   -3.8558   49.0000 
+2714.1250    8.5000    8.5718   51.4738   73.8787    2.3556    0.1239   76.3367   -3.7591   49.0000 
+2714.2250    8.5000    8.6127   51.8503   74.4927    2.3617    0.1237   75.9082   -3.6403   49.0000 
+2714.3250    8.5000    8.6127   50.7901   73.5567    2.3677    0.1225   75.5459   -3.5633   49.0000 
+2714.4250    8.5000    8.6127   49.6607   71.6894    2.3690    0.1205   75.4133   -3.6053   49.0000 
+2714.5250    8.5000    8.6127   48.6620   69.8795    2.3678    0.1174   75.4439   -3.7302   49.0000 
+2714.6250    8.5000    8.5636   48.3163   68.0322    2.3679    0.1152   75.4541   -3.8022   49.0000 
+2714.7250    8.5000    8.5636   49.6377   66.8216    2.3701    0.1125   75.2959   -3.8468   49.0000 
+2714.8250    8.5000    8.5554   51.4124   66.1245    2.3767    0.1099   74.9077   -3.8030   49.0000 
+2714.9250    8.5000    8.5881   52.9335   65.5781    2.3853    0.1072   74.6046   -3.7218   49.0000 
+2715.0250    8.5000    8.5963   53.9938   64.6373    2.4031    0.1051   74.5923   -3.4346   49.0000 
+2715.1250    8.5000    8.6290   53.6557   63.3841    2.4230    0.1043   74.9066   -3.0645   49.0000 
+2715.2250    8.5000    8.6290   53.4252   62.7066    2.4389    0.1034   75.4515   -2.7748   49.0000 
+2715.3250    8.5000    8.6127   53.4329   62.9951    2.4363    0.1034   75.9403   -2.8272   49.0000 
+2715.4250    8.5000    8.5963   53.6250   63.5751    2.4203    0.1039   76.3505   -3.1312   49.0000 
+2715.5250    8.5000    8.5718   55.5994   63.2371    2.4008    0.1058   76.6582   -3.4586   49.0000 
+2715.6250    8.5000    8.6127   57.2589   61.6990    2.3862    0.1080   76.8571   -3.6746   49.0000 
+2715.7250    8.5000    8.5881   58.1501   60.4987    2.3731    0.1103   76.9643   -3.8595   49.0000 
+2715.8250    8.5000    8.6209   58.7570   60.7082    2.3592    0.1114   76.9235   -4.1035   49.0000 
+2715.9250    8.5000    8.6290   58.0195   62.3466    2.3507    0.1112   76.7704   -4.2799   49.0000 
+2716.0250    8.5000    8.5963   56.2678   64.9804    2.3513    0.1093   76.5357   -4.3328   49.0000 
+2716.1250    8.5000    8.6209   54.5700   68.1657    2.3575    0.1076   76.2806   -4.2631   49.0000 
+2716.2250    8.5000    8.6045   52.3189   72.4257    2.3616    0.1063   76.1071   -4.2245   49.0000 
+2716.3250    8.5000    8.6127   49.9219   77.0476    2.3613    0.1066   76.0153   -4.2188   49.0000 
+2716.4250    8.5000    8.6209   48.2010   80.5114    2.3603    0.1074   76.0000   -4.2139   49.0000 
+2716.5250    8.5000    8.6045   46.2496   81.5687    2.3586    0.1087   76.0000   -4.2044   49.0000 
+2716.6250    8.5000    8.6045   44.8207   81.2589    2.3612    0.1091   76.0000   -4.1414   49.0000 
+2716.7250    8.5000    8.6045   43.7835   81.5890    2.3619    0.1090   76.0000   -4.1284   49.0000 
+2716.8250    8.5000    8.6045   43.2611   82.9491    2.3682    0.1094   76.0000   -3.9904   49.0000 
+2716.9250    8.5000    8.6127   43.7067   84.8075    2.3722    0.1105   76.0612   -3.8732   49.0000 
+2717.0250    8.5000    8.5963   45.1894   86.5548    2.3830    0.1114   76.2857   -3.6256   49.0000 
+2717.1250    8.5000    8.6209   47.6632   88.1235    2.3883    0.1113   76.5714   -3.5245   49.0000 
+2717.2250    8.5000    8.6290   50.8592   89.5625    2.3933    0.1111   76.8367   -3.4301   49.0000 
+2717.3250    8.5000    8.6290   53.6404   89.3775    2.3928    0.1109   76.8367   -3.4464   49.0000 
+2717.4250    8.5000    8.6209   55.1615   86.7354    2.3931    0.1121   76.5714   -3.4026   49.0000 
+2717.5250    8.5000    8.6045   55.8299   81.9487    2.3900    0.1131   76.2908   -3.4299   49.0000 
+2717.6250    8.5000    8.6045   55.0002   76.8209    2.3841    0.1151   76.1378   -3.4805   49.0000 
+2717.7250    8.5000    8.6127   53.8632   72.7438    2.3789    0.1162   76.2281   -3.5468   49.0000 
+2717.8250    8.5000    8.6290   53.8555   70.0008    2.3786    0.1178   76.4260   -3.4998   49.0000 
+2717.9250    8.5000    8.6372   52.8490   68.7318    2.3818    0.1186   76.5117   -3.4096   49.0000 
+2718.0250    8.5000    8.6290   53.0949   68.0327    2.3835    0.1191   76.3571   -3.3580   49.0000 
+2718.1250    8.5000    8.6454   55.1538   67.4138    2.3827    0.1190   76.0214   -3.3807   49.0000 
+2718.2250    8.5000    8.6290   55.5226   65.9175    2.3824    0.1183   75.5816   -3.4094   49.0000 
+2718.3250    8.5000    8.6045   56.9977   64.1924    2.3831    0.1174   75.1980   -3.4261   49.0000 
+2718.4250    8.5000    8.6127   57.7967   62.3115    2.3815    0.1153   74.8393   -3.5255   49.0000 
+2718.5250    8.5000    8.6045   55.9067   60.4498    2.3756    0.1136   74.5112   -3.7011   49.0000 
+2718.6250    8.5000    8.6045   55.4688   58.5538    2.3702    0.1130   74.4975   -3.8276   49.0000 
+2718.7250    8.5000    8.6127   55.3920   56.8967    2.3731    0.1130   74.7122   -3.7709   49.0000 
+2718.8250    8.5000    8.6045   53.9938   55.8462    2.3816    0.1130   75.1347   -3.5998   49.0000 
+2718.9250    8.5000    8.6045   53.2716   55.5614    2.3858    0.1105   75.4561   -3.6013   49.0000 
+2719.0250    8.5000    8.6209   52.0039   56.1427    2.3816    0.1061   75.4776   -3.8301   49.0000 
+2719.1250    8.5000    8.6290   49.1460   57.0682    2.3737    0.0985   75.3750   -4.2405   49.0000 
+2719.2250    8.5000    8.6045   47.1562   58.3300    2.3783    0.0896   75.1265   -4.4485   49.0000 
+2719.3250    8.5000    8.6209   46.1882   59.4483    2.4014    0.0820   74.8755   -4.2392   49.0000 
+2719.4250    8.5000    8.5800   44.9589   61.2562    2.4425    0.0773   74.5408   -3.5725   49.0000 
+2719.5250    8.5000    8.5963   44.8821   63.1276    2.4735    0.0775   74.2367   -2.9477   49.0000 
+2719.6250    8.5000    8.5718   46.0499   65.2556    2.4759    0.0810   74.1245   -2.7808   49.0000 
+2719.7250    8.5000    8.5636   46.6568   66.5311    2.4452    0.0877   74.4480   -3.1726   49.0000 
+2719.8250    8.5000    8.5718   48.0166   66.6709    2.4115    0.0948   75.2036   -3.6097   49.0000 
+2719.9250    8.5000    8.5636   50.2216   65.4447    2.3870    0.1013   76.1362   -3.8842   49.0000 
+2720.0250    8.5000    8.5800   51.3279   63.0703    2.3806    0.1050   76.8061   -3.8876   49.0000 
+2720.1250    8.5000    8.6045   51.9425   61.0266    2.3780    0.1062   76.9653   -3.9000   49.0000 
+2720.2250    8.5000    8.6127   51.8042   59.8863    2.3808    0.1048   76.7163   -3.8909   49.0000 
+2720.3250    8.5000    8.6372   49.9219   60.1635    2.3792    0.1028   76.4745   -3.9898   49.0000 
+2720.4250    8.5000    8.6290   48.1933   61.1009    2.3728    0.1008   76.3980   -4.1833   49.0000 
+2720.5250    8.5000    8.6290   47.7554   61.9459    2.3620    0.0990   76.3418   -4.4596   49.0000 
+2720.6250    8.5000    8.6209   48.1549   62.5431    2.3540    0.0979   76.0153   -4.6552   49.0000 
+2720.7250    8.5000    8.5963   49.8067   62.7240    2.3570    0.0980   75.2602   -4.5956   49.0000 
+2720.8250    8.5000    8.6209   51.4892   62.9157    2.3674    0.0996   74.3214   -4.3307   49.0000 
+2720.9250    8.5000    8.6127   52.4111   62.6967    2.3853    0.1014   73.4337   -3.9129   49.0000 
+2721.0250    8.5000    8.6127   52.2267   62.5379    2.4024    0.1031   72.7194   -3.5148   49.0000 
+2721.1250    8.5000    8.6209   51.2203   62.4338    2.4124    0.1051   72.4796   -3.2477   49.0000 
+2721.2250    8.5000    8.5881   50.2523   62.6178    2.4071    0.1085   72.6122   -3.2425   49.0000 
+2721.3250    8.5000    8.5718   49.0231   63.0147    2.3883    0.1124   73.2250   -3.4890   49.0000 
+2721.4250    8.5000    8.5718   48.5237   63.7883    2.3715    0.1157   74.1158   -3.7139   49.0000 
+2721.5250    8.5000    8.5636   48.7388   65.1796    2.3649    0.1180   75.0842   -3.7665   49.0000 
+2721.6250    8.5000    8.5800   49.6607   67.1098    2.3682    0.1206   75.8852   -3.6171   49.0000 
+2721.7250    8.5000    8.6045   51.3356   68.9304    2.3676    0.1225   76.4107   -3.5662   49.0000 
+2721.8250    8.5000    8.6209   53.8862   69.4814    2.3638    0.1224   76.6893   -3.6445   49.0000 
+2721.9250    8.5000    8.6454   56.0220   68.9591    2.3584    0.1185   76.8423   -3.8805   49.0000 
+2722.0250    8.5000    8.6372   57.2666   67.8283    2.3614    0.1141   77.0010   -3.9670   49.0000 
+2722.1250    8.5000    8.6209   57.6200   67.1154    2.3677    0.1121   77.2250   -3.9089   49.0000 
+2722.2250    8.5000    8.5800   56.0758   65.9671    2.3794    0.1136   77.3301   -3.6259   49.0000 
+2722.3250    8.5000    8.6045   54.5930   64.4404    2.3893    0.1149   77.1617   -3.3831   49.0000 
+2722.4250    8.5000    8.5963   52.6723   62.2498    2.3952    0.1132   76.6214   -3.3212   49.0000 
+2722.5250    8.5000    8.5963   51.6121   60.3223    2.3941    0.1100   75.7602   -3.4503   49.0000 
+2722.6250    8.5000    8.5963   51.5507   59.6974    2.3891    0.1082   74.9031   -3.6111   49.0000 
+2722.7250    8.5000    8.5963   50.7978   60.7287    2.3845    0.1085   74.2949   -3.6930   49.0000 
+2722.8250    8.5000    8.6290   50.8976   63.5679    2.3779    0.1104   74.0454   -3.7605   49.0000 
+2722.9250    8.5000    8.6454   49.6377   66.8425    2.3706    0.1114   74.1709   -3.8748   49.0000 
+2723.0250    8.5000    8.6290   48.8233   69.3577    2.3663    0.1132   74.5291   -3.9028   49.0000 
+2723.1250    8.5000    8.6209   49.0308   70.2208    2.3690    0.1133   75.0275   -3.8438   49.0000 
+2723.2250    8.5000    8.6045   49.6146   69.4691    2.3722    0.1128   75.4765   -3.7981   49.0000 
+2723.3250    8.5000    8.6045   52.2575   68.0579    2.3719    0.1109   75.7622   -3.8653   49.0000 
+2723.4250    8.5000    8.6127   54.2857   66.6756    2.3685    0.1091   75.8862   -3.9931   49.0000 
+2723.5250    8.5000    8.6127   55.6839   66.1463    2.3683    0.1082   75.8801   -4.0254   49.0000 
+2723.6250    8.5000    8.6209   55.5303   66.7063    2.3713    0.1055   75.7852   -4.0576   49.0000 
+2723.7250    8.5000    8.6290   53.3638   68.0011    2.3721    0.1025   75.6219   -4.1427   49.0000 
+2723.8250    8.5000    8.6290   50.9130   69.0792    2.3718    0.0984   75.4209   -4.2826   49.0000 
+2723.9250    8.5000    8.6699   49.1998   69.5146    2.3703    0.0974   75.2525   -4.3477   49.0000 
+2724.0250    8.5000    8.6290   49.7222   69.2266    2.3737    0.0976   75.2393   -4.2737   49.0000 
+2724.1250    8.5000    8.6781   51.2434   68.7314    2.3775    0.1004   75.3209   -4.1034   49.0000 
+2724.2250    8.5000    8.6863   52.7338   68.0511    2.3816    0.1025   75.5485   -3.9516   49.0000 
+2724.3250    8.5000    8.6454   54.5315   67.1362    2.3809    0.1048   75.7168   -3.8878   49.0000 
+2724.4250    8.5000    8.6454   54.4394   65.9922    2.3764    0.1050   75.7189   -3.9734   49.0000 
+2724.5250    8.5000    8.6209   54.7774   64.7020    2.3714    0.1052   75.5903   -4.0662   49.0000 
+2724.6250    8.5000    8.6045   55.3382   63.7075    2.3720    0.1045   75.2934   -4.0749   49.0000 
+2724.7250    8.5000    8.5881   53.8401   63.4012    2.3784    0.1048   74.9872   -3.9377   49.0000 
+2724.8250    8.5000    8.6290   52.4572   63.8637    2.3879    0.1049   74.8046   -3.7444   49.0000 
+2724.9250    8.5000    8.6536   49.9604   65.0988    2.3930    0.1058   74.7633   -3.6155   49.0000 
+2725.0250    8.5000    8.6536   47.5173   66.1346    2.3952    0.1062   74.9439   -3.5544   49.0000 
+2725.1250    8.5000    8.6372   46.1959   67.1875    2.3911    0.1061   75.4102   -3.6398   49.0000 
+2725.2250    8.5000    8.6127   45.1356   67.6806    2.3839    0.1056   75.8520   -3.8020   49.0000 
+2725.3250    8.5000    8.6127   45.1971   67.8159    2.3766    0.1040   76.2964   -4.0027   49.0000 
+2725.4250    8.5000    8.6536   45.7810   66.5447    2.3726    0.1024   76.4827   -4.1337   49.0000 
+2725.5250    8.5000    8.6536   47.2714   64.4526    2.3750    0.1007   76.5526   -4.1450   49.0000 
+2725.6250    8.5000    8.6699   49.2075   62.6769    2.3773    0.1010   76.5224   -4.0876   49.0000 
+2725.7250    8.5000    8.6536   49.6607   62.0159    2.3807    0.1026   76.5663   -3.9663   49.0000 
+2725.8250    8.5000    8.6127   49.5993   62.3045    2.3819    0.1053   76.6571   -3.8516   49.0000 
+2725.9250    8.5000    8.5800   48.1857   62.4906    2.3811    0.1064   76.6092   -3.8302   49.0000 
+2726.0250    8.5000    8.5800   46.6799   62.1507    2.3798    0.1057   76.3995   -3.8811   49.0000 
+2726.1250    8.5000    8.5881   46.5877   61.6358    2.3756    0.1037   75.9474   -4.0308   49.0000 
+2726.2250    8.5000    8.5881   46.6491   61.3265    2.3791    0.1022   75.7056   -4.0117   49.0000 
+2726.3250    8.5000    8.6290   48.1549   61.5111    2.3815    0.1012   75.6699   -3.9961   49.0000 
+2726.4250    8.5000    8.6454   50.6979   61.9637    2.3900    0.1006   75.8500   -3.8479   49.0000 
+2726.5250    8.5000    8.6536   53.2024   62.2738    2.3913    0.1004   75.8561   -3.8272   49.0000 
+2726.6250    8.5000    8.6536   56.2140   62.6662    2.3942    0.1014   75.6449   -3.7355   49.0000 
+2726.7250    8.5000    8.6372   57.8581   62.9565    2.3915    0.1028   75.3622   -3.7435   49.0000 
+2726.8250    8.5000    8.6045   57.6891   63.1349    2.3879    0.1037   75.1582   -3.7855   49.0000 
+2726.9250    8.5000    8.6045   56.4368   62.4514    2.3832    0.1035   75.1071   -3.8849   49.0000 
+2727.0250    8.5000    8.5963   54.3472   61.3955    2.3782    0.1019   75.0133   -4.0378   49.0000 
+2727.1250    8.5000    8.6209   52.8183   60.6456    2.3783    0.0996   74.7939   -4.1142   49.0000 
+2727.2250    8.5000    8.6372   50.8285   60.7053    2.3790    0.0970   74.5082   -4.1881   49.0000 
+2727.3250    8.5000    8.7027   49.9143   61.3361    2.3857    0.0952   74.2908   -4.1141   49.0000 
+2727.4250    8.5000    8.7272   49.7299   62.4402    2.3900    0.0941   74.1628   -4.0653   49.0000 
+2727.5250    8.5000    8.7108   50.5366   63.4870    2.3950    0.0925   74.0735   -4.0158   49.0000 
+2727.6250    8.5000    8.6618   54.2242   63.9915    2.3954    0.0922   74.0102   -4.0171   49.0000 
+2727.7250    8.5000    8.6290   57.9964   62.8729    2.3932    0.0931   73.9327   -4.0325   49.0000 
+2727.8250    8.5000    8.6127   61.6380   60.1122    2.3854    0.0968   73.8704   -4.0639   49.0000 
+2727.9250    8.5000    8.6127   64.3500   56.5818    2.3768    0.1012   73.8071   -4.0924   49.0000 
+2728.0250    8.5000    8.6209   65.1336   53.0389    2.3721    0.1061   73.7684   -4.0208   49.0000 
+2728.1250    8.5000    8.6127   65.7252   50.0420    2.3760    0.1094   73.9087   -3.8337   49.0000 
+2728.2250    8.5000    8.6127   65.2489   47.9231    2.3831    0.1109   74.1638   -3.6415   49.0000 
+2728.3250    8.5000    8.6290   63.4434   46.6978    2.3890    0.1105   74.4454   -3.5370   49.0000 
+2728.4250    8.5000    8.6618   60.4165   46.1730    2.3906    0.1092   74.5413   -3.5494   49.0000 
+2728.5250    8.5000    8.6536   55.4227   46.1472    2.3943    0.1076   74.5286   -3.5259   49.0000 
+2728.6250    8.5000    8.6536   50.6287   46.4583    2.3956    0.1052   74.5031   -3.5805   49.0000 
+2728.7250    8.5000    8.5963   47.6171   47.2332    2.3969    0.1026   74.5643   -3.6415   49.0000 
+2728.8250    8.5000    8.5881   47.3098   48.1814    2.3929    0.0994   74.5051   -3.8291   49.0000 
+2728.9250    8.5000    8.5718   49.8144   48.8366    2.3958    0.0980   74.0898   -3.8172   49.0000 
+2729.0250    8.5000    8.5718   54.1474   48.6637    2.4050    0.0981   73.4296   -3.6290   49.0000 
+2729.1250    8.5000    8.5800   59.7865   47.4187    2.4135    0.1001   72.8893   -3.3941   49.0000 
+2729.2250    8.5000    8.5718   65.3679   45.4833    2.4165    0.1021   72.6949   -3.2648   49.0000 
+2729.3250    8.5000    8.5800   71.7138   42.9080    2.4123    0.1052   72.8439   -3.2475   49.0000 
+2729.4250    8.5000    8.6045   78.0827   39.7880    2.4231    0.1096   73.1908   -2.8837   49.0000 
+2729.5250    8.5000    8.6045   81.6321   35.9652    2.4520    0.1157   73.6102   -2.1037   49.0000 
+2729.6250    8.5000    8.6209   82.8383   31.7265    2.4966    0.1222   74.0020   -0.9963   25.0000 
+2729.7250    8.5000    8.5881   80.8408   27.5024    2.5313    0.1288   74.4597   -0.0816   54.0000 
+2729.8250    8.5000    8.6045   76.3465   23.9468    2.5402    0.1332   74.7770    0.2429   54.0000 
+2729.9250    8.5000    8.5800   71.8752   21.4356    2.5245    0.1340   74.9276   -0.0437   54.0000 
+2730.0250    8.5000    8.5800   68.6676   20.0259    2.5009    0.1295   74.9643   -0.6672   25.0000 
+2730.1250    8.5000    8.5718   66.5626   19.5115    2.4798    0.1236   74.8092   -1.2825   49.0000 
+2730.2250    8.5000    8.5963   65.1336   19.4863    2.4660    0.1188   74.7561   -1.7203   49.0000 
+2730.3250    8.5000    8.5963   65.1490   19.5343    2.4576    0.1164   74.5898   -1.9687   49.0000 
+2730.4250    8.5000    8.5881   64.9108   19.3330    2.4546    0.1142   74.4372   -2.1017   49.0000 
+2730.5250    8.5000    8.5963   63.6278   18.9030    2.4609    0.1113   74.2806   -2.0733   49.0000 
+2730.6250    8.5000    8.6045   62.8980   18.4226    2.4680    0.1091   74.2000   -2.0027   49.0000 
+2730.7250    8.5000    8.6045   61.1770   18.1494    2.4778    0.1074   74.4321   -1.8616   49.0000 
+2730.8250    8.5000    8.6290   58.7801   18.2388    2.4746    0.1063   74.7214   -1.9655   49.0000 
+2730.9250    8.5000    8.6127   58.9836   18.8207    2.4631    0.1040   75.0908   -2.2730   49.0000 
+2731.0250    8.5000    8.6372   59.9286   19.8850    2.4468    0.1026   75.2638   -2.6459   49.0000 
+2731.1250    8.5000    8.6209   61.9031   21.2156    2.4379    0.1035   75.1515   -2.7916   49.0000 
+2731.2250    8.5000    8.6209   65.9365   22.2076    2.4423    0.1075   74.8240   -2.5698   49.0000 
+2731.3250    8.5000    8.6290   68.8866   22.1055    2.4533    0.1135   74.2332   -2.1495   49.0000 
+2731.4250    8.5000    8.6045   71.6524   20.8400    2.4695    0.1189   73.7816   -1.6456   49.0000 
+2731.5250    8.5000    8.5881   74.2798   19.1542    2.4829    0.1234   73.6934   -1.2286   49.0000 
+2731.6250    8.5000    8.5881   75.9547   17.7773    2.4927    0.1261   73.9622   -0.9434   25.0000 
+2731.7250    8.5000    8.5800   76.6499   16.9218    2.4983    0.1293   74.4770   -0.7242   25.0000 
+2731.8250    8.5000    8.5963   76.5885   16.4662    2.5046    0.1331   74.7199   -0.4710   25.0000 
+2731.9250    8.5000    8.6209   76.2812   16.2075    2.5132    0.1383   74.6107   -0.1251   54.0000 
+2732.0250    8.5000    8.6127   74.2376   16.0041    2.5212    0.1423   74.2546    0.1679   54.0000 
+2732.1250    8.5000    8.6045   71.5794   15.8891    2.5241    0.1425   73.9056    0.2318   54.0000 
+2732.2250    8.5000    8.6127   67.3232   16.1022    2.5158    0.1379   73.8352   -0.0880   54.0000 
+2732.3250    8.5000    8.6127   62.1451   16.9291    2.4990    0.1306   73.9531   -0.6682   25.0000 
+2732.4250    8.5000    8.6045   58.7954   18.4928    2.4741    0.1248   74.0714   -1.3584   49.0000 
+2732.5250    8.5000    8.6290   58.8262   20.5441    2.4573    0.1221   74.3429   -1.7840   49.0000 
+2732.6250    8.5000    8.6372   62.4831   22.3729    2.4484    0.1221   74.6413   -1.9603   49.0000 
+2732.7250    8.5000    8.6618   69.0671   22.9364    2.4559    0.1240   74.9495   -1.7469   49.0000 
+2732.8250    8.5000    8.6536   77.4873   22.0139    2.4714    0.1294   75.0903   -1.2594   49.0000 
+2732.9250    8.5000    8.6372   82.9420   20.2280    2.4968    0.1374   74.5760   -0.4860   25.0000 
+2733.0250    8.5000    8.6290   85.4158   18.7449    2.5241    0.1436   73.5015    0.2694   54.0000 
+2733.1250    8.5000    8.6372   82.7577   18.7078    2.5510    0.1409   71.7903    0.7165   57.0000 
+2733.2250    8.5000    8.6618   74.2030   20.9650    2.5698    0.1277   70.0403    0.6516   57.0000 
+2733.3250    8.5000    8.6536   64.1848   26.7458    2.5714    0.1088   68.7092    0.0542   54.0000 
+2733.4250    8.5000    8.6372   53.4099   37.2562    2.5498    0.0915   68.1888   -0.9561   25.0000 
+2733.5250    8.5000    8.6454   44.9128   52.1229    2.5158    0.0801   68.2653   -2.0149   49.0000 
+2733.6250    8.5000    8.6290   39.8346   62.8885    2.4822    0.0738   68.5816   -2.8945   49.0000 
+2733.7250    8.5000    8.6209   38.0676   66.5271    2.4623    0.0707   68.8571   -3.3967   49.0000 
+2733.8250    8.5000    8.6372   37.9677   69.5341    2.4513    0.0684   68.8929   -3.6952   49.0000 
+2733.9250    8.5000    8.6863   38.0445   73.2128    2.4510    0.0658   68.9133   -3.7867   49.0000 
+2734.0250    8.5000    8.7190   37.4261   77.2147    2.4550    0.0626   68.8566   -3.8144   49.0000 
+2734.1250    8.5000    8.7681   35.4132   81.2180    2.4604    0.0585   68.8102   -3.8438   49.0000 
+2734.2250    8.5000    8.7517   34.0419   84.2987    2.4663    0.0544   68.6408   -3.8629   49.0000 
+2734.3250    8.5000    8.7190   34.4030   85.2480    2.4747    0.0507   68.3184   -3.8165   49.0000 
+2734.4250    8.5000    8.6863   36.4773   84.6874    2.4910    0.0489   67.9357   -3.5490   49.0000 
+2734.5250    8.5000    8.6290   39.8116   82.9609    2.5061    0.0490   67.7122   -3.2441   49.0000 
+2734.6250    8.5000    8.6290   43.0075   81.1981    2.5113    0.0514   67.6724   -3.0623   49.0000 
+2734.7250    8.5000    8.6372   45.3892   80.8632    2.4981    0.0553   67.8464   -3.1957   49.0000 
+2734.8250    8.5000    8.6618   47.5634   82.0457    2.4725    0.0603   68.3112   -3.5407   49.0000 
+2734.9250    8.5000    8.6781   49.4994   83.5608    2.4471    0.0660   69.0255   -3.8587   49.0000 
+2735.0250    8.5000    8.7190   52.2882   80.1285    2.4295    0.0724   70.0429   -3.9960   49.0000 
+2735.1250    8.5000    8.6699   55.5533   69.5501    2.4242    0.0803   71.2867   -3.8387   49.0000 
+2735.2250    8.5000    8.6372   58.3345   57.3981    2.4292    0.0890   72.5444   -3.4494   49.0000 
+2735.3250    8.5000    8.5800   60.1360   47.4821    2.4392    0.0967   73.6342   -2.9920   49.0000 
+2735.4250    8.5000    8.5636   60.0592   40.5450    2.4484    0.1025   74.2827   -2.6155   49.0000 
+2735.5250    8.5000    8.5718   57.5854   35.8722    2.4511    0.1055   74.4306   -2.4606   49.0000 
+2735.6250    8.5000    8.5636   54.2127   33.3523    2.4531    0.1051   74.1888   -2.4348   49.0000 
+2735.7250    8.5000    8.5472   50.4789   32.7649    2.4507    0.1001   73.5918   -2.6496   49.0000 
+2735.8250    8.5000    8.5800   47.2061   34.0282    2.4451    0.0925   72.7531   -3.0154   49.0000 
+2735.9250    8.5000    8.5963   45.7310   36.7956    2.4292    0.0850   71.8648   -3.5838   49.0000 
+2736.0250    8.5000    8.6127   44.5633   40.4065    2.4134    0.0809   71.1046   -4.0361   49.0000 
+2736.1250    8.5000    8.6290   43.9525   43.8586    2.4050    0.0796   70.8898   -4.2479   49.0000 
+2736.2250    8.5000    8.6045   44.2291   46.4626    2.4102    0.0811   71.2245   -4.0922   49.0000 
+2736.3250    8.5000    8.6045   44.6055   47.2740    2.4155    0.0842   71.8536   -3.8838   49.0000 
+2736.4250    8.5000    8.6127   46.7644   45.8575    2.4121    0.0880   72.4311   -3.8254   49.0000 
+2736.5250    8.5000    8.6127   51.3048   42.4452    2.4035    0.0916   72.7281   -3.8784   49.0000 
+2736.6250    8.5000    8.6127   55.0616   37.9458    2.4044    0.0936   72.9025   -3.7902   49.0000 
+2736.7250    8.5000    8.5963   58.8569   32.6745    2.4233    0.0965   73.2515   -3.3168   49.0000 
+2736.8250    8.5000    8.5800   62.2680   27.9968    2.4532    0.1000   73.6281   -2.6023   49.0000 
+2736.9250    8.5000    8.5800   61.9146   24.5043    2.4787    0.1051   73.9995   -1.9239   49.0000 
+2737.0250    8.5000    8.5718   61.4075   22.4896    2.4802    0.1089   74.2291   -1.7665   49.0000 
+2737.1250    8.5000    8.5636   60.1860   21.8574    2.4530    0.1126   74.5281   -2.1869   49.0000 
+2737.2250    8.5000    8.5718   56.4023   22.5224    2.4123    0.1156   75.2658   -2.9008   49.0000 
+2737.3250    8.5000    8.5718   54.0053   24.3595    2.3834    0.1176   76.3357   -3.4096   49.0000 
+2737.4250    8.5000    8.5800   50.9937   27.4509    2.3746    0.1155   77.1500   -3.6584   49.0000 
+2737.5250    8.5000    8.5963   48.0051   31.8125    2.3758    0.1095   77.2061   -3.8348   49.0000 
+2737.6250    8.5000    8.5800   46.3994   37.6791    2.3759    0.1008   76.5051   -4.1206   49.0000 
+2737.7250    8.5000    8.5636   44.5095   44.6328    2.3785    0.0925   75.4423   -4.3465   49.0000 
+2737.8250    8.5000    8.5472   44.6632   52.1188    2.3890    0.0863   74.6719   -4.3419   49.0000 
+2737.9250    8.5000    8.5391   44.6094   59.5586    2.4023    0.0832   74.1923   -4.1820   49.0000 
+2738.0250    8.5000    8.5636   45.2970   66.6459    2.4079    0.0826   74.0378   -4.0886   49.0000 
+2738.1250    8.5000    8.6045   46.2957   73.2851    2.4034    0.0824   74.0429   -4.1859   49.0000 
+2738.2250    8.5000    8.6209   45.0819   79.8134    2.3959    0.0830   74.0561   -4.3159   49.0000 
+2738.3250    8.5000    8.6290   44.5364   85.9007    2.3943    0.0839   73.9653   -4.3182   49.0000 
+2738.4250    8.5000    8.6209   42.9999   90.5404    2.3956    0.0862   73.6878   -4.2131   49.0000 
+2738.5250    8.5000    8.5963   41.5709   94.6168    2.3935    0.0879   73.4816   -4.2016   49.0000 
+2738.6250    8.5000    8.5963   41.8859   98.9757    2.3819    0.0893   73.4459   -4.3839   49.0000 
+2738.7250    8.5000    8.5881   41.6784  104.4014    2.3705    0.0896   73.6556   -4.6048   49.0000 
+2738.8250    8.5000    8.5963   41.7399  110.5248    2.3689    0.0897   74.0087   -4.6325   49.0000 
+2738.9250    8.5000    8.6045   41.4710  114.7972    2.3783    0.0887   74.3684   -4.4780   49.0000 
+2739.0250    8.5000    8.5963   40.2418  115.5570    2.3891    0.0875   74.7184   -4.3001   49.0000 
+2739.1250    8.5000    8.5881   39.6579  109.4651    2.3947    0.0868   74.9735   -4.2131   49.0000 
+2739.2250    8.5000    8.5718   40.4876   98.6954    2.3981    0.0875   75.0143   -4.1217   49.0000 
+2739.3250    8.5000    8.5800   43.7720   86.5049    2.4011    0.0895   75.0699   -3.9959   49.0000 
+2739.4250    8.5000    8.5881   48.6966   75.6429    2.4075    0.0931   75.2245   -3.7463   49.0000 
+2739.5250    8.5000    8.6045   53.6288   67.2919    2.4164    0.0984   75.6878   -3.3917   49.0000 
+2739.6250    8.5000    8.6045   56.5636   61.4423    2.4240    0.1056   76.2036   -2.9995   49.0000 
+2739.7250    8.5000    8.5881   56.4868   58.2042    2.4226    0.1135   76.5423   -2.7653   49.0000 
+2739.8250    8.5000    8.5881   54.3971   57.8533    2.4062    0.1194   76.7505   -2.8964   49.0000 
+2739.9250    8.5000    8.5800   51.9924   61.3322    2.3856    0.1222   76.8842   -3.2157   49.0000 
+2740.0250    8.5000    8.5636   50.3330   69.1335    2.3653    0.1214   77.2133   -3.6482   49.0000 
+2740.1250    8.5000    8.5800   48.9309   80.9908    2.3502    0.1203   77.6225   -3.9875   49.0000 
+2740.2250    8.5000    8.5881   48.0397   92.4031    2.3347    0.1188   78.0306   -4.3469   49.0000 
+2740.3250    8.5000    8.6290   47.2561   97.6885    2.3246    0.1179   78.3929   -4.5784   49.0000 
+2740.4250    8.5000    8.6290   46.5185   96.4825    2.3271    0.1159   78.7551   -4.5931   49.0000 
+2740.5250    8.5000    8.6372   46.4417   93.3742    2.3345    0.1145   79.1939   -4.4921   49.0000 
+2740.6250    8.5000    8.6290   46.3111   91.8291    2.3422    0.1136   79.7265   -4.3690   49.0000 
+2740.7250    8.5000    8.6127   45.6888   92.3510    2.3413    0.1135   80.3163   -4.3887   49.0000 
+2740.8250    8.5000    8.6045   45.4430   93.8806    2.3400    0.1136   80.7735   -4.4133   49.0000 
+2740.9250    8.5000    8.5800   45.3815   93.7288    2.3352    0.1136   81.0673   -4.5106   49.0000 
+2741.0250    8.5000    8.5636   45.3354   91.2243    2.3312    0.1135   81.1296   -4.5928   49.0000 
+2741.1250    8.5000    8.5472   45.9654   88.0773    2.3315    0.1140   81.0704   -4.5701   49.0000 
+2741.2250    8.5000    8.5472   46.0268   86.0399    2.3386    0.1141   80.9296   -4.4251   49.0000 
+2741.3250    8.5000    8.5636   45.9193   86.3928    2.3482    0.1146   80.7607   -4.2146   49.0000 
+2741.4250    8.5000    8.5718   47.0102   88.4725    2.3542    0.1149   80.6189   -4.0874   49.0000 
+2741.5250    8.5000    8.5800   47.9629   91.4746    2.3563    0.1162   80.5709   -3.9983   49.0000 
+2741.6250    8.5000    8.5963   49.3918   93.6480    2.3582    0.1168   80.6536   -3.9417   49.0000 
+2741.7250    8.5000    8.5963   50.9591   93.7794    2.3591    0.1175   80.7903   -3.9005   49.0000 
+2741.8250    8.5000    8.6127   51.2664   92.6222    2.3608    0.1181   80.9469   -3.8491   49.0000 
+2741.9250    8.5000    8.6290   50.7747   91.7684    2.3580    0.1188   81.0592   -3.8788   49.0000 
+2742.0250    8.5000    8.6454   49.3611   91.9674    2.3530    0.1195   81.0474   -3.9555   49.0000 
+2742.1250    8.5000    8.6372   47.6556   93.3978    2.3447    0.1196   80.7020   -4.1198   49.0000 
+2742.2250    8.5000    8.6045   45.7426   94.5599    2.3391    0.1200   79.9786   -4.2175   49.0000 
+2742.3250    8.5000    8.5800   45.1280   95.0995    2.3353    0.1203   79.0760   -4.2834   49.0000 
+2742.4250    8.5000    8.5718   45.1433   94.0883    2.3367    0.1200   78.3097   -4.2654   49.0000 
+2742.5250    8.5000    8.5718   45.6658   91.8203    2.3396    0.1190   78.0112   -4.2394   49.0000 
+2742.6250    8.5000    8.5636   46.4801   88.6690    2.3481    0.1166   77.9122   -4.1522   49.0000 
+2742.7250    8.5000    8.5472   46.7260   85.4111    2.3511    0.1141   77.7071   -4.1759   49.0000 
+2742.8250    8.5000    8.5391   47.8169   83.2537    2.3528    0.1124   77.2046   -4.1965   49.0000 
+2742.9250    8.5000    8.5391   48.8617   82.2400    2.3513    0.1125   76.5622   -4.2232   49.0000 
+2743.0250    8.5000    8.5554   50.0756   82.2184    2.3582    0.1133   76.1230   -4.0587   49.0000 
+2743.1250    8.5000    8.5554   51.0590   81.7642    2.3645    0.1124   75.9444   -3.9618   49.0000 
+2743.2250    8.5000    8.5636   50.2216   81.3422    2.3733    0.1099   76.0117   -3.8719   49.0000 
+2743.3250    8.5000    8.5718   48.0359   81.0937    2.3783    0.1068   76.1525   -3.8744   49.0000 
+2743.4250    8.5000    8.5636   46.2535   82.1854    2.3878    0.1051   76.2597   -3.7383   49.0000 
+2743.5250    8.5000    8.5718   44.6862   84.5670    2.3895    0.1049   76.2730   -3.7135   49.0000 
+2743.6250    8.5000    8.5963   44.4250   87.7365    2.3842    0.1049   76.1755   -3.8197   49.0000 
+2743.7250    8.5000    8.6127   45.6773   89.7549    2.3713    0.1042   76.1755   -4.0995   49.0000 
+2743.8250    8.5000    8.6045   46.8220   89.8698    2.3607    0.1035   76.3526   -4.3346   49.0000 
+2743.9250    8.5000    8.5881   47.5518   87.4928    2.3596    0.1029   76.7372   -4.3774   49.0000 
+2744.0250    8.5000    8.5718   47.9052   84.8043    2.3665    0.1031   77.1250   -4.2345   49.0000 
+2744.1250    8.5000    8.5472   48.3316   81.7282    2.3791    0.1039   77.2403   -3.9540   49.0000 
+2744.2250    8.5000    8.5554   49.1767   79.7556    2.3894    0.1050   77.0556   -3.7139   49.0000 
+2744.3250    8.5000    8.5636   50.7670   77.6585    2.3926    0.1057   76.7056   -3.6260   49.0000 
+2744.4250    8.5000    8.5636   52.2114   76.0234    2.3938    0.1052   76.4291   -3.6161   49.0000 
+2744.5250    8.5000    8.5881   52.9720   74.7299    2.3914    0.1045   76.3878   -3.6890   49.0000 
+2744.6250    8.5000    8.5800   52.1653   74.8072    2.3901    0.1040   76.5510   -3.7299   49.0000 
+2744.7250    8.5000    8.5800   50.4751   75.6760    2.3854    0.1034   76.7755   -3.8463   49.0000 
+2744.8250    8.5000    8.5718   49.8374   76.6318    2.3811    0.1028   76.9847   -3.9528   49.0000 
+2744.9250    8.5000    8.5718   49.8528   76.3539    2.3775    0.1022   77.2061   -4.0438   49.0000 
+2745.0250    8.5000    8.5800   51.6044   75.2378    2.3714    0.1033   77.5980   -4.1286   49.0000 
+2745.1250    8.5000    8.5800   54.8696   73.4641    2.3643    0.1059   78.1602   -4.1856   49.0000 
+2745.2250    8.5000    8.5881   59.0336   71.7098    2.3565    0.1092   78.7714   -4.2321   49.0000 
+2745.3250    8.5000    8.6045   62.1604   69.8024    2.3569    0.1117   79.0796   -4.1366   49.0000 
+2745.4250    8.5000    8.6045   62.8826   67.7847    2.3625    0.1127   78.9602   -3.9918   49.0000 
+2745.5250    8.5000    8.6127   61.9530   66.1665    2.3743    0.1141   78.5939   -3.7093   49.0000 
+2745.6250    8.5000    8.6209   56.4676   65.5997    2.3811    0.1152   78.2459   -3.5379   49.0000 
+2745.7250    8.5000    8.6209   50.5366   66.7142    2.3850    0.1162   78.0173   -3.4248   49.0000 
+2745.8250    8.5000    8.6290   47.0179   69.1190    2.3804    0.1142   77.8163   -3.5837   49.0000 
+2745.9250    8.5000    8.6045   44.1138   71.8643    2.3763    0.1116   77.4796   -3.7542   49.0000 
+2746.0250    8.5000    8.5718   44.4673   74.1432    2.3708    0.1088   77.0378   -3.9589   49.0000 
+2746.1250    8.5000    8.5636   46.2957   76.0824    2.3676    0.1081   76.7770   -4.0454   49.0000 
+2746.2250    8.5000    8.5472   46.3726   78.3467    2.3631    0.1085   76.8153   -4.1222   49.0000 
+2746.3250    8.5000    8.5554   46.0345   81.3155    2.3631    0.1093   77.1459   -4.0944   49.0000 
+2746.4250    8.5000    8.5554   45.5428   84.5595    2.3672    0.1087   77.6204   -4.0331   49.0000 
+2746.5250    8.5000    8.5636   44.1599   87.1123    2.3734    0.1063   77.9796   -3.9874   49.0000 
+2746.6250    8.5000    8.5963   43.8065   87.4529    2.3723    0.1039   78.0281   -4.0919   49.0000 
+2746.7250    8.5000    8.6209   44.2214   86.0575    2.3627    0.1017   77.6311   -4.3568   49.0000 
+2746.8250    8.5000    8.6209   44.3751   84.1289    2.3559    0.1002   76.9622   -4.5423   49.0000 
+2746.9250    8.5000    8.5881   45.2816   83.4581    2.3572    0.0984   76.3015   -4.5739   49.0000 
+2747.0250    8.5000    8.5554   46.0960   83.6155    2.3705    0.0979   75.9025   -4.3253   49.0000 
+2747.1250    8.5000    8.5554   46.9641   83.8154    2.3815    0.0990   75.8332   -4.0708   49.0000 
+2747.2250    8.5000    8.5554   47.5480   83.3781    2.3911    0.1015   75.9036   -3.7939   49.0000 
+2747.3250    8.5000    8.5636   47.3636   82.6393    2.3942    0.1048   76.0459   -3.6239   49.0000 
+2747.4250    8.5000    8.5636   46.8566   82.7313    2.3952    0.1078   76.2296   -3.5018   49.0000 
+2747.5250    8.5000    8.5718   44.6440   84.7491    2.3908    0.1107   76.4643   -3.4940   49.0000 
+2747.6250    8.5000    8.5963   41.6170   88.9648    2.3834    0.1126   76.7469   -3.5786   49.0000 
+2747.7250    8.5000    8.6127   39.1355   94.4699    2.3706    0.1137   77.0265   -3.7978   49.0000 
+2747.8250    8.5000    8.6045   36.9767   98.4644    2.3570    0.1140   77.3061   -4.0610   49.0000 
+2747.9250    8.5000    8.6209   36.7462  100.8697    2.3445    0.1139   77.5765   -4.3132   49.0000 
+2748.0250    8.5000    8.6045   38.4056  102.0751    2.3397    0.1130   77.7245   -4.4394   49.0000 
+2748.1250    8.5000    8.5963   39.6195  103.2429    2.3402    0.1111   77.7102   -4.4928   49.0000 
+2748.2250    8.5000    8.6045   40.9255  104.7082    2.3481    0.1086   77.5464   -4.4180   49.0000 
+2748.3250    8.5000    8.5800   41.8475  105.4464    2.3550    0.1066   77.3464   -4.3455   49.0000 
+2748.4250    8.5000    8.5881   43.3994  105.0471    2.3580    0.1055   77.2219   -4.3220   49.0000 
+2748.5250    8.5000    8.5718   46.8489  100.6408    2.3502    0.1043   77.1791   -4.5203   49.0000 
+2748.6250    8.5000    8.5636   51.0052   93.6665    2.3452    0.1032   77.0888   -4.6553   49.0000 
+2748.7250    8.5000    8.5636   54.9157   86.8599    2.3484    0.1027   77.0275   -4.6075   49.0000 
+2748.8250    8.5000    8.5554   56.4676   82.6703    2.3636    0.1043   77.0857   -4.2499   49.0000 
+2748.9250    8.5000    8.5963   55.1308   81.6018    2.3809    0.1061   77.2148   -3.8447   49.0000 
+2749.0250    8.5000    8.5881   51.8272   82.5877    2.3952    0.1071   77.3995   -3.5255   49.0000 
+2749.1250    8.5000    8.5963   48.5698   84.8874    2.4048    0.1058   77.4000   -3.3770   49.0000 
+2749.2250    8.5000    8.5963   45.9731   87.1664    2.4044    0.1040   76.9439   -3.4438   49.0000 
+2749.3250    8.5000    8.5963   45.7426   87.9991    2.3965    0.1027   76.4663   -3.6455   49.0000 
+2749.4250    8.5000    8.6127   47.7247   85.6644    2.3879    0.1028   75.8969   -3.8137   49.0000 
+2749.5250    8.5000    8.6290   49.3842   79.5783    2.3899    0.1050   75.5388   -3.7036   49.0000 
+2749.6250    8.5000    8.6209   50.8900   71.1761    2.4040    0.1096   75.2694   -3.2664   49.0000 
+2749.7250    8.5000    8.6290   50.2216   63.3891    2.4127    0.1143   75.0061   -2.9339   49.0000 
+2749.8250    8.5000    8.6127   47.4635   58.4085    2.4107    0.1169   74.9158   -2.8890   49.0000 
+2749.9250    8.5000    8.6045   44.9589   56.9920    2.3931    0.1148   74.9495   -3.3108   49.0000 
+2750.0250    8.5000    8.5963   43.6683   58.4351    2.3791    0.1115   75.1684   -3.7035   49.0000 
+2750.1250    8.5000    8.5554   43.7144   61.3233    2.3717    0.1082   75.3878   -3.9576   49.0000 
+2750.2250    8.5000    8.5554   45.4506   64.6414    2.3754    0.1070   75.5510   -3.9237   49.0000 
+2750.3250    8.5000    8.5636   48.0627   67.9893    2.3794    0.1080   75.6582   -3.8113   49.0000 
+2750.4250    8.5000    8.5718   49.2536   71.5901    2.3829    0.1088   75.6327   -3.7155   49.0000 
+2750.5250    8.5000    8.6127   50.0756   74.7404    2.3841    0.1093   75.4439   -3.6732   49.0000 
+2750.6250    8.5000    8.6536   49.3304   77.4539    2.3870    0.1071   75.0714   -3.6896   49.0000 
+2750.7250    8.5000    8.6536   46.4110   79.4104    2.3857    0.1056   74.7444   -3.7668   49.0000 
+2750.8250    8.5000    8.6781   44.2752   81.2575    2.3836    0.1040   74.6622   -3.8620   49.0000 
+2750.9250    8.5000    8.6618   41.6631   82.2779    2.3818    0.1039   74.8878   -3.9019   49.0000 
+2751.0250    8.5000    8.5963   40.2495   82.7394    2.3855    0.1037   75.3500   -3.8351   49.0000 
+2751.1250    8.5000    8.5963   41.0485   82.9653    2.3880    0.1038   75.8408   -3.7823   49.0000 
+2751.2250    8.5000    8.5718   42.0549   83.8149    2.3853    0.1028   76.3760   -3.8680   49.0000 
+2751.3250    8.5000    8.5718   44.5902   84.8293    2.3794    0.1009   76.8821   -4.0498   49.0000 
+2751.4250    8.5000    8.5963   47.1101   85.2947    2.3732    0.0987   77.3633   -4.2451   49.0000 
+2751.5250    8.5000    8.5718   48.7542   84.7252    2.3729    0.0963   77.5867   -4.3313   49.0000 
+2751.6250    8.5000    8.5881   48.8925   83.7111    2.3735    0.0921   77.4500   -4.4593   49.0000 
+2751.7250    8.5000    8.6127   46.8796   83.2012    2.3794    0.0844   76.7816   -4.5977   49.0000 
+2751.8250    8.5000    8.6127   43.8219   83.7821    2.3938    0.0757   75.8541   -4.6022   49.0000 
+2751.9250    8.5000    8.6045   40.0651   84.9391    2.4257    0.0689   74.9342   -4.1889   49.0000 
+2752.0250    8.5000    8.5800   37.6681   86.1515    2.4671    0.0673   74.2291   -3.4161   49.0000 
+2752.1250    8.5000    8.5800   36.2391   86.5983    2.4933    0.0708   73.9332   -2.7743   49.0000 
+2752.2250    8.5000    8.5718   35.2557   86.7756    2.4832    0.0789   73.9786   -2.7067   49.0000 
+2752.3250    8.5000    8.5636   35.0099   85.5123    2.4417    0.0876   74.4755   -3.2452   49.0000 
+2752.4250    8.5000    8.5718   35.0867   83.4899    2.3960    0.0945   75.2959   -3.9277   49.0000 
+2752.5250    8.5000    8.5800   36.3390   80.8489    2.3678    0.0979   76.2469   -4.3785   49.0000 
+2752.6250    8.5000    8.5800   38.8589   79.3274    2.3589    0.0999   77.0602   -4.4927   49.0000 
+2752.7250    8.5000    8.5718   41.7169   79.1188    2.3572    0.1006   77.4837   -4.5023   49.0000 
+2752.8250    8.5000    8.5718   43.6836   80.0929    2.3558    0.1012   77.5449   -4.5097   49.0000 
+2752.9250    8.5000    8.5554   45.0358   81.1497    2.3539    0.1011   77.3102   -4.5537   49.0000 
+2753.0250    8.5000    8.5636   45.6811   81.5491    2.3572    0.1013   77.0122   -4.4801   49.0000 
+2753.1250    8.5000    8.5718   46.5416   81.1089    2.3631    0.1009   76.7398   -4.3732   49.0000 
+2753.2250    8.5000    8.5718   48.3547   80.2662    2.3691    0.1008   76.5036   -4.2596   49.0000 
+2753.3250    8.5000    8.5800   49.8989   79.4661    2.3713    0.1001   76.4464   -4.2371   49.0000 
+2753.4250    8.5000    8.6127   50.5212   78.0860    2.3768    0.1006   76.4643   -4.1114   49.0000 
+2753.5250    8.5000    8.5963   50.7133   75.9754    2.3866    0.1015   76.7041   -3.8841   49.0000 
+2753.6250    8.5000    8.6045   51.0052   73.1138    2.3983    0.1038   77.0367   -3.5731   49.0000 
+2753.7250    8.5000    8.6045   50.9668   70.2584    2.4038    0.1061   77.3949   -3.3860   49.0000 
+2753.8250    8.5000    8.5636   51.9886   67.2448    2.3991    0.1085   77.6837   -3.4020   49.0000 
+2753.9250    8.5000    8.5636   52.1806   64.3054    2.3894    0.1096   77.8311   -3.5586   49.0000 
+2754.0250    8.5000    8.5554   50.7517   60.9517    2.3765    0.1101   77.8679   -3.7982   49.0000 
+2754.1250    8.5000    8.5391   49.8144   57.6853    2.3720    0.1101   77.7663   -3.8911   49.0000 
+2754.2250    8.5000    8.5554   49.2382   54.5918    2.3743    0.1098   77.5204   -3.8553   49.0000 
+2754.3250    8.5000    8.5718   51.3279   51.9816    2.3862    0.1094   77.1281   -3.6295   49.0000 
+2754.4250    8.5000    8.5800   54.7236   50.0715    2.4024    0.1099   76.6934   -3.2885   49.0000 
+2754.5250    8.5000    8.5800   57.7122   49.1571    2.4195    0.1125   76.3036   -2.8604   49.0000 
+2754.6250    8.5000    8.5800   58.9798   49.6308    2.4350    0.1159   76.1525   -2.4361   49.0000 
+2754.7250    8.5000    8.5881   56.0988   51.7116    2.4357    0.1188   76.2189   -2.3285   49.0000 
+2754.8250    8.5000    8.5963   52.4111   55.5541    2.4244    0.1182   76.2724   -2.5720   49.0000 
+2754.9250    8.5000    8.5881   48.2932   61.1368    2.4007    0.1155   76.1480   -3.1344   49.0000 
+2755.0250    8.5000    8.5963   44.1907   68.1094    2.3838    0.1113   75.7944   -3.6163   49.0000 
+2755.1250    8.5000    8.5800   41.8551   75.0982    2.3707    0.1090   75.5184   -3.9522   49.0000 
+2755.2250    8.5000    8.5718   39.7117   80.8228    2.3661    0.1080   75.5173   -4.0788   49.0000 
+2755.3250    8.5000    8.5718   38.9127   84.3063    2.3596    0.1084   75.6949   -4.1954   49.0000 
+2755.4250    8.5000    8.5718   39.6118   85.6493    2.3572    0.1086   75.7939   -4.2354   49.0000 
+2755.5250    8.5000    8.5800   41.0562   85.7505    2.3597    0.1093   75.8117   -4.1628   49.0000 
+2755.6250    8.5000    8.5718   42.5005   85.6482    2.3669    0.1096   75.6934   -4.0074   49.0000 
+2755.7250    8.5000    8.5800   43.3533   86.1947    2.3724    0.1092   75.6633   -3.9110   49.0000 
+2755.8250    8.5000    8.5554   44.3520   86.9387    2.3713    0.1075   75.5061   -3.9919   49.0000 
+2755.9250    8.5000    8.5636   45.0435   86.7723    2.3694    0.1062   75.2138   -4.0736   49.0000 
+2756.0250    8.5000    8.5963   45.8348   84.8457    2.3689    0.1055   74.9867   -4.1052   49.0000 
+2756.1250    8.5000    8.5881   46.7490   79.7668    2.3682    0.1061   74.8082   -4.0982   49.0000 
+2756.2250    8.5000    8.6045   47.9245   70.5878    2.3666    0.1067   75.0168   -4.1138   49.0000 
+2756.3250    8.5000    8.5963   52.9489   57.7246    2.3696    0.1073   75.4337   -4.0310   49.0000 
+2756.4250    8.5000    8.5800   62.1758   44.6386    2.3824    0.1093   76.0413   -3.7094   49.0000 
+2756.5250    8.5000    8.5881   73.4309   34.2667    2.4053    0.1130   76.6592   -3.1283   49.0000 
+2756.6250    8.5000    8.5881   83.3953   27.8179    2.4370    0.1195   77.0036   -2.2774   49.0000 
+2756.7250    8.5000    8.6045   85.8614   24.9539    2.4698    0.1277   76.9276   -1.3468   49.0000 
+2756.8250    8.5000    8.6045   80.6372   25.4225    2.4857    0.1342   76.5031   -0.8126   25.0000 
+2756.9250    8.5000    8.6045   69.7663   29.5006    2.4737    0.1325   75.9148   -1.1104   49.0000 
+2757.0250    8.5000    8.5963   57.9042   37.8660    2.4429    0.1202   75.3602   -2.1363   49.0000 
+2757.1250    8.5000    8.5881   49.6531   49.9763    2.4208    0.1034   74.9398   -3.1364   49.0000 
+2757.2250    8.5000    8.6045   45.9731   60.4820    2.4121    0.0901   74.7143   -3.7547   49.0000 
+2757.3250    8.5000    8.6127   47.6171   62.6523    2.4146    0.0846   74.5888   -3.8902   49.0000 
+2757.4250    8.5000    8.6045   50.8900   59.4357    2.4150    0.0848   74.7112   -3.8743   49.0000 
+2757.5250    8.5000    8.6127   54.1628   55.3587    2.4188    0.0898   75.1704   -3.6300   49.0000 
+2757.6250    8.5000    8.5881   55.8069   53.7752    2.4163    0.0970   75.8235   -3.4391   49.0000 
+2757.7250    8.5000    8.5800   53.6404   55.3534    2.4111    0.1043   76.5770   -3.3036   49.0000 
+2757.8250    8.5000    8.5718   50.6441   60.0904    2.3956    0.1077   77.0281   -3.4967   49.0000 
+2757.9250    8.5000    8.5718   48.0781   67.4181    2.3868    0.1077   77.0944   -3.6743   49.0000 
+2758.0250    8.5000    8.5636   45.4199   74.9358    2.3805    0.1059   76.9138   -3.8604   49.0000 
+2758.1250    8.5000    8.5718   44.9589   80.5506    2.3835    0.1046   76.5913   -3.8426   49.0000 
+2758.2250    8.5000    8.5881   45.3200   82.8759    2.3798    0.1037   76.4148   -3.9484   49.0000 
+2758.3250    8.5000    8.6372   45.3584   85.4048    2.3734    0.1029   76.3934   -4.1016   49.0000 
+2758.4250    8.5000    8.6290   45.9039   89.8924    2.3621    0.1017   76.5255   -4.3695   49.0000 
+2758.5250    8.5000    8.6209   45.4430   97.1398    2.3527    0.1013   76.7592   -4.5699   49.0000 
+2758.6250    8.5000    8.5800   44.0754  103.8882    2.3466    0.1018   77.0832   -4.6741   49.0000 
+2758.7250    8.5000    8.5391   42.0472  105.9598    2.3468    0.1039   77.4087   -4.6024   49.0000 
+2758.8250    8.5000    8.5309   40.5414  104.0667    2.3551    0.1056   77.6750   -4.3765   49.0000 
+2758.9250    8.5000    8.5472   39.9806   99.4927    2.3624    0.1060   77.8332   -4.2196   49.0000 
+2759.0250    8.5000    8.5554   40.4876   94.9736    2.3633    0.1044   77.8985   -4.2530   49.0000 
+2759.1250    8.5000    8.5718   41.0638   90.7341    2.3534    0.1033   77.9138   -4.4869   49.0000 
+2759.2250    8.5000    8.5718   41.6400   87.6091    2.3424    0.1033   77.9291   -4.7087   49.0000 
+2759.3250    8.5000    8.5718   42.9461   84.8028    2.3333    0.1040   77.8133   -4.8669   49.0000 
+2759.4250    8.5000    8.5881   44.3981   81.9668    2.3348    0.1039   77.5265   -4.8404   49.0000 
+2759.5250    8.5000    8.6045   46.9103   78.6382    2.3376    0.1031   77.0786   -4.8105   49.0000 
+2759.6250    8.5000    8.6045   50.0065   75.1790    2.3429    0.1019   76.7143   -4.7444   49.0000 
+2759.7250    8.5000    8.6045   52.5187   71.9749    2.3405    0.1011   76.6684   -4.8201   49.0000 
+2759.8250    8.5000    8.6127   54.4240   69.4419    2.3408    0.1010   76.8827   -4.8166   49.0000 
+2759.9250    8.5000    8.6045   56.0297   67.8432    2.3429    0.1015   77.2138   -4.7588   49.0000 
+2760.0250    8.5000    8.6045   56.1142   67.1560    2.3471    0.1014   77.3903   -4.6780   49.0000 
+2760.1250    8.5000    8.5881   54.8235   67.2508    2.3502    0.1014   77.4566   -4.6156   49.0000 
+2760.2250    8.5000    8.5800   53.2870   68.0246    2.3502    0.1022   77.5199   -4.5906   49.0000 
+2760.3250    8.5000    8.6045   50.9898   69.2541    2.3564    0.1046   77.6750   -4.3862   49.0000 
+2760.4250    8.5000    8.6045   48.3547   71.5133    2.3659    0.1060   77.8148   -4.1483   49.0000 
+2760.5250    8.5000    8.6127   46.1421   74.8750    2.3751    0.1063   77.8383   -3.9571   49.0000 
+2760.6250    8.5000    8.5963   43.1919   79.3325    2.3806    0.1052   77.7888   -3.8824   49.0000 
+2760.7250    8.5000    8.5636   40.3340   83.5675    2.3818    0.1046   77.6628   -3.8756   49.0000 
+2760.8250    8.5000    8.5636   39.2430   86.6579    2.3849    0.1054   77.6577   -3.7875   49.0000 
+2760.9250    8.5000    8.5636   39.4505   88.6997    2.3839    0.1067   77.7138   -3.7663   49.0000 
+2761.0250    8.5000    8.5554   41.1099   89.9728    2.3790    0.1092   77.8036   -3.7802   49.0000 
+2761.1250    8.5000    8.5800   43.1305   90.9238    2.3688    0.1109   77.8934   -3.9278   49.0000 
+2761.2250    8.5000    8.5718   43.7220   90.5178    2.3570    0.1125   77.9403   -4.1101   49.0000 
+2761.3250    8.5000    8.5718   42.4313   89.1841    2.3483    0.1121   77.9719   -4.2984   49.0000 
+2761.4250    8.5000    8.5881   40.1573   86.9989    2.3450    0.1104   77.9429   -4.4215   49.0000 
+2761.5250    8.5000    8.5636   37.6527   85.6881    2.3492    0.1086   77.8163   -4.3955   49.0000 
+2761.6250    8.5000    8.5718   36.5311   86.2252    2.3549    0.1077   77.6020   -4.3121   49.0000 
+2761.7250    8.5000    8.5636   36.9997   89.2830    2.3597    0.1085   77.3061   -4.1905   49.0000 
+2761.8250    8.5000    8.5391   38.2827   94.6440    2.3597    0.1083   77.0000   -4.1954   49.0000 
+2761.9250    8.5000    8.5554   39.9345  101.3798    2.3587    0.1064   76.7092   -4.2801   49.0000 
+2762.0250    8.5000    8.5881   40.5337  107.7854    2.3556    0.1027   76.5327   -4.4626   49.0000 
+2762.1250    8.5000    8.6045   41.1868  112.0922    2.3554    0.0991   76.5811   -4.5896   49.0000 
+2762.2250    8.5000    8.6127   40.7719  112.8094    2.3548    0.0973   76.7934   -4.6593   49.0000 
+2762.3250    8.5000    8.6045   40.4492  109.0728    2.3600    0.0957   77.0577   -4.6095   49.0000 
+2762.4250    8.5000    8.5800   40.7412  101.9875    2.3635    0.0945   77.1689   -4.5806   49.0000 
+2762.5250    8.5000    8.5800   40.6029   93.4964    2.3709    0.0931   77.2444   -4.4785   49.0000 
+2762.6250    8.5000    8.5963   42.2623   85.3935    2.3765    0.0941   77.3811   -4.3320   49.0000 
+2762.7250    8.5000    8.5800   44.3059   78.6977    2.3841    0.0966   77.5423   -4.0971   49.0000 
+2762.8250    8.5000    8.5718   47.3559   73.7349    2.3889    0.0997   77.7143   -3.8982   49.0000 
+2762.9250    8.5000    8.5554   50.3599   70.3078    2.3885    0.1010   77.6673   -3.8649   49.0000 
+2763.0250    8.5000    8.5391   52.2959   68.2547    2.3828    0.1019   77.5954   -3.9453   49.0000 
+2763.1250    8.5000    8.5636   52.9259   67.9319    2.3738    0.1032   77.6148   -4.0853   49.0000 
+2763.2250    8.5000    8.5800   50.4981   69.0907    2.3691    0.1066   77.7179   -4.0639   49.0000 
+2763.3250    8.5000    8.5800   48.1473   71.4104    2.3706    0.1097   77.8587   -3.9318   49.0000 
+2763.4250    8.5000    8.5800   46.1959   74.0904    2.3759    0.1109   77.9179   -3.7841   49.0000 
+2763.5250    8.5000    8.5718   45.2586   76.0017    2.3757    0.1083   77.9112   -3.8767   49.0000 
+2763.6250    8.5000    8.5881   46.8335   77.2955    2.3703    0.1039   77.8786   -4.1312   49.0000 
+2763.7250    8.5000    8.6045   47.5173   77.7922    2.3643    0.1003   77.7801   -4.3701   49.0000 
+2763.8250    8.5000    8.6045   47.6018   78.0551    2.3636    0.1003   77.6097   -4.3856   49.0000 
+2763.9250    8.5000    8.6127   47.4020   78.0479    2.3651    0.1018   77.4158   -4.3032   49.0000 
+2764.0250    8.5000    8.6045   46.5723   78.7026    2.3657    0.1032   77.3383   -4.2474   49.0000 
+2764.1250    8.5000    8.6127   47.4328   79.9526    2.3615    0.1027   77.3801   -4.3466   49.0000 
+2764.2250    8.5000    8.5963   48.4392   81.2955    2.3554    0.1023   77.4648   -4.4817   49.0000 
+2764.3250    8.5000    8.5963   49.1537   81.8574    2.3509    0.1025   77.4577   -4.5638   49.0000 
+2764.4250    8.5000    8.5881   49.2920   81.6490    2.3548    0.1022   77.3046   -4.4975   49.0000 
+2764.5250    8.5000    8.6045   48.3163   80.3865    2.3631    0.1012   77.1189   -4.3644   49.0000 
+2764.6250    8.5000    8.6127   47.8784   77.8598    2.3703    0.0996   76.9719   -4.2752   49.0000 
+2764.7250    8.5000    8.6127   48.6543   73.5805    2.3733    0.0982   76.8816   -4.2611   49.0000 
+2764.8250    8.5000    8.6290   50.2984   68.7366    2.3730    0.0971   76.7689   -4.3052   49.0000 
+2764.9250    8.5000    8.6127   52.1269   64.3341    2.3749    0.0953   76.5888   -4.3231   49.0000 
+2765.0250    8.5000    8.6209   53.2870   61.3056    2.3787    0.0938   76.3551   -4.2993   49.0000 
+2765.1250    8.5000    8.6290   53.1026   58.9770    2.3865    0.0925   76.2071   -4.1869   49.0000 
+2765.2250    8.5000    8.6290   51.9579   57.2368    2.3899    0.0937   76.2245   -4.0798   49.0000 
+2765.3250    8.5000    8.6045   50.9668   56.1091    2.3881    0.0965   76.3969   -4.0208   49.0000 
+2765.4250    8.5000    8.5718   50.2062   56.1028    2.3817    0.1003   76.7383   -4.0213   49.0000 
+2765.5250    8.5000    8.5636   50.6518   56.6413    2.3778    0.1029   77.0867   -4.0146   49.0000 
+2765.6250    8.5000    8.5718   52.8337   57.1991    2.3748    0.1038   77.4133   -4.0423   49.0000 
+2765.7250    8.5000    8.5800   54.7082   57.5001    2.3747    0.1031   77.5663   -4.0685   49.0000 
+2765.8250    8.5000    8.6045   56.6135   58.3123    2.3734    0.1025   77.4439   -4.1137   49.0000 
+2765.9250    8.5000    8.6209   56.8901   59.8976    2.3755    0.1032   77.0796   -4.0502   49.0000 
+2766.0250    8.5000    8.6127   54.9080   61.9151    2.3717    0.1051   76.6485   -4.0650   49.0000 
+2766.1250    8.5000    8.5881   52.5340   63.4823    2.3668    0.1053   76.4776   -4.1532   49.0000 
+2766.2250    8.5000    8.5636   50.1371   64.1580    2.3585    0.1041   76.6327   -4.3608   49.0000 
+2766.3250    8.5000    8.5472   49.2382   63.8624    2.3546    0.1025   77.0694   -4.4895   49.0000 
+2766.4250    8.5000    8.5554   49.3534   62.8815    2.3525    0.1034   77.5306   -4.5036   49.0000 
+2766.5250    8.5000    8.5472   49.7299   61.0492    2.3514    0.1056   77.8301   -4.4529   49.0000 
+2766.6250    8.5000    8.5718   49.4994   59.5347    2.3469    0.1091   77.9648   -4.4267   49.0000 
+2766.7250    8.5000    8.5800   47.5096   58.7733    2.3401    0.1118   77.9725   -4.4723   49.0000 
+2766.8250    8.5000    8.5881   45.2970   59.5178    2.3310    0.1138   77.8270   -4.5884   49.0000 
+2766.9250    8.5000    8.5881   43.8987   61.5370    2.3251    0.1136   77.5270   -4.7123   49.0000 
+2767.0250    8.5000    8.5554   42.5773   65.0503    2.3237    0.1126   77.1556   -4.7731   49.0000 
+2767.1250    8.5000    8.5718   42.3084   70.7668    2.3285    0.1103   76.8352   -4.7519   49.0000 
+2767.2250    8.5000    8.5554   42.3392   78.2138    2.3340    0.1068   76.6173   -4.7612   49.0000 
+2767.3250    8.5000    8.5963   41.7015   86.1834    2.3388    0.1016   76.4163   -4.8369   49.0000 
+2767.4250    8.5000    8.6045   41.6631   91.0103    2.3448    0.0968   75.9704   -4.8757   49.0000 
+2767.5250    8.5000    8.5800   41.7169   92.4882    2.3574    0.0942   75.3607   -4.7113   49.0000 
+2767.6250    8.5000    8.5881   42.1087   90.4446    2.3719    0.0932   74.7464   -4.4562   49.0000 
+2767.7250    8.5000    8.5554   42.7463   87.4873    2.3865    0.0924   74.2566   -4.1913   49.0000 
+2767.8250    8.5000    8.5800   43.7989   85.4919    2.3957    0.0909   73.9250   -4.0564   49.0000 
+2767.9250    8.5000    8.5800   44.4903   86.4645    2.4041    0.0900   73.5587   -3.9158   49.0000 
+2768.0250    8.5000    8.6045   44.3213   91.2887    2.4081    0.0897   73.1745   -3.8482   49.0000 
+2768.1250    8.5000    8.6127   43.4224  100.7932    2.4086    0.0879   72.8520   -3.8979   49.0000 
+2768.2250    8.5000    8.5881   41.6477  112.0055    2.4038    0.0841   72.8444   -4.1203   49.0000 
+2768.3250    8.5000    8.6209   40.9716  120.4333    2.3958    0.0796   73.2158   -4.4319   49.0000 
+2768.4250    8.5000    8.5963   41.2175  122.5637    2.3875    0.0779   73.8444   -4.6520   49.0000 
+2768.5250    8.5000    8.5963   42.3622  116.5449    2.3827    0.0795   74.5128   -4.6954   49.0000 
+2768.6250    8.5000    8.5800   43.5377  106.2214    2.3801    0.0842   75.1372   -4.5897   49.0000 
+2768.7250    8.5000    8.5800   43.3302   95.0354    2.3789    0.0898   75.6668   -4.4294   49.0000 
+2768.8250    8.5000    8.6045   42.7771   87.2518    2.3761    0.0966   76.3617   -4.2576   49.0000 
+2768.9250    8.5000    8.6045   42.1240   82.8907    2.3781    0.1012   77.0485   -4.0644   49.0000 
+2769.0250    8.5000    8.5881   42.5543   80.5246    2.3825    0.1038   77.6046   -3.8886   49.0000 
+2769.1250    8.5000    8.5800   44.5134   78.4516    2.3895    0.1030   77.8260   -3.7759   49.0000 
+2769.2250    8.5000    8.5718   46.7874   76.2399    2.3881    0.1025   77.6117   -3.8208   49.0000 
+2769.3250    8.5000    8.5881   49.9680   74.7203    2.3826    0.1025   77.2378   -3.9302   49.0000 
+2769.4250    8.5000    8.6045   52.6262   73.9550    2.3733    0.1029   76.9367   -4.1018   49.0000 
+2769.5250    8.5000    8.6045   52.9950   73.6781    2.3726    0.1027   76.8847   -4.1248   49.0000 
+2769.6250    8.5000    8.5718   52.2114   73.3899    2.3732    0.1018   77.0444   -4.1445   49.0000 
+2769.7250    8.5000    8.5718   49.5378   73.1787    2.3743    0.1007   77.3117   -4.1588   49.0000 
+2769.8250    8.5000    8.5636   46.0960   72.9710    2.3735    0.1008   77.4240   -4.1698   49.0000 
+2769.9250    8.5000    8.5472   44.7054   71.7233    2.3778    0.1016   77.4653   -4.0569   49.0000 
+2770.0250    8.5000    8.5800   43.9909   69.5374    2.3866    0.1037   77.4577   -3.8110   49.0000 
+2770.1250    8.5000    8.5718   43.9448   67.2501    2.3884    0.1043   77.4265   -3.7551   49.0000 
+2770.2250    8.5000    8.5963   45.3431   67.0564    2.3830    0.1045   77.4806   -3.8559   49.0000 
+2770.3250    8.5000    8.6045   46.2496   69.1073    2.3734    0.1041   77.4066   -4.0605   49.0000 
+2770.4250    8.5000    8.5800   48.1703   70.7086    2.3734    0.1038   77.1617   -4.0732   49.0000 
+2770.5250    8.5000    8.5881   50.7747   71.1754    2.3813    0.1028   76.7689   -3.9484   49.0000 
+2770.6250    8.5000    8.6045   52.0039   69.9478    2.3933    0.1001   76.2929   -3.7958   49.0000 
+2770.7250    8.5000    8.6045   52.7722   69.7252    2.4028    0.0979   75.8163   -3.6808   49.0000 
+2770.8250    8.5000    8.6127   52.1730   70.2653    2.4067    0.0968   75.3429   -3.6384   49.0000 
+2770.9250    8.5000    8.6045   49.9757   72.3156    2.4111    0.0984   74.8372   -3.4977   49.0000 
+2771.0250    8.5000    8.5963   47.2637   76.1201    2.4151    0.1002   74.3985   -3.3584   49.0000 
+2771.1250    8.5000    8.6127   44.4826   81.4256    2.4178    0.0998   74.1117   -3.3189   49.0000 
+2771.2250    8.5000    8.6045   41.5555   87.0713    2.4121    0.0969   74.0383   -3.5256   49.0000 
+2771.3250    8.5000    8.5963   39.0894   92.7619    2.4018    0.0931   74.1525   -3.8604   49.0000 
+2771.4250    8.5000    8.5963   36.4005   98.4722    2.3968    0.0906   74.3719   -4.0433   49.0000 
+2771.5250    8.5000    8.5800   33.3965  104.4804    2.3968    0.0885   74.6505   -4.1134   49.0000 
+2771.6250    8.5000    8.5800   31.3069  109.3245    2.3974    0.0870   74.9357   -4.1521   49.0000 
+2771.7250    8.5000    8.5636   31.7294  111.6155    2.3920    0.0857   75.2367   -4.3021   49.0000 
+2771.8250    8.5000    8.5881   34.9868  109.1915    2.3884    0.0846   75.6092   -4.4117   49.0000 
+2771.9250    8.5000    8.5881   39.9959  101.6058    2.3892    0.0845   75.9969   -4.3997   49.0000 
+2772.0250    8.5000    8.5881   44.2675   91.3956    2.3935    0.0848   76.3878   -4.3039   49.0000 
+2772.1250    8.5000    8.5963   46.4571   80.9739    2.3938    0.0866   76.6383   -4.2358   49.0000 
+2772.2250    8.5000    8.5800   47.5480   72.7488    2.3926    0.0881   76.7270   -4.2123   49.0000 
+2772.3250    8.5000    8.5718   48.5621   67.1936    2.3907    0.0907   76.6597   -4.1622   49.0000 
+2772.4250    8.5000    8.5718   51.2741   64.0626    2.3918    0.0936   76.4699   -4.0426   49.0000 
+2772.5250    8.5000    8.5718   53.6250   62.5716    2.3963    0.0979   76.2832   -3.8105   49.0000 
+2772.6250    8.5000    8.5636   54.8389   62.4625    2.4006    0.1002   76.1240   -3.6479   49.0000 
+2772.7250    8.5000    8.5881   53.5789   63.0324    2.4039    0.1022   76.0597   -3.5157   49.0000 
+2772.8250    8.5000    8.6209   50.7440   64.3557    2.4001    0.1018   76.0765   -3.6052   49.0000 
+2772.9250    8.5000    8.5881   48.1242   66.1722    2.3952    0.1008   76.1378   -3.7364   49.0000 
+2773.0250    8.5000    8.6045   45.7887   68.2944    2.3876    0.0980   76.1684   -3.9799   49.0000 
+2773.1250    8.5000    8.5800   45.0972   70.8904    2.3807    0.0962   76.0204   -4.1784   49.0000 
+2773.2250    8.5000    8.5718   44.5594   74.0318    2.3739    0.0959   75.7520   -4.3258   49.0000 
+2773.3250    8.5000    8.5800   44.5441   78.0399    2.3697    0.0963   75.3459   -4.3959   49.0000 
+2773.4250    8.5000    8.5963   45.4506   81.8826    2.3735    0.0957   74.8459   -4.3405   49.0000 
+2773.5250    8.5000    8.5881   46.3341   84.6211    2.3832    0.0938   74.3546   -4.2095   49.0000 
+2773.6250    8.5000    8.5963   48.2394   84.9320    2.3977    0.0927   73.9628   -3.9555   49.0000 
+2773.7250    8.5000    8.6045   49.6223   83.7791    2.4044    0.0926   73.8974   -3.8254   49.0000 
+2773.8250    8.5000    8.5963   50.0910   81.4554    2.3974    0.0935   74.2219   -3.9361   49.0000 
+2773.9250    8.5000    8.5963   50.3138   78.6068    2.3784    0.0938   74.6525   -4.3046   49.0000 
+2774.0250    8.5000    8.6045   48.7849   75.7032    2.3606    0.0948   75.0179   -4.6294   49.0000 
+2774.1250    8.5000    8.5800   47.4865   73.6951    2.3556    0.0951   75.1648   -4.7162   49.0000 
+2774.2250    8.5000    8.6209   47.1639   72.0691    2.3585    0.0949   75.1643   -4.6685   49.0000 
+2774.3250    8.5000    8.6209   47.1255   70.1567    2.3631    0.0934   75.2184   -4.6266   49.0000 
+2774.4250    8.5000    8.6045   47.7093   67.7903    2.3691    0.0919   75.1888   -4.5550   49.0000 
+2774.5250    8.5000    8.6290   48.7388   65.5158    2.3834    0.0903   75.0051   -4.3231   49.0000 
+2774.6250    8.5000    8.6045   48.4085   64.1678    2.4114    0.0872   74.6235   -3.8664   49.0000 
+2774.7250    8.5000    8.6209   47.4404   64.1368    2.4470    0.0820   74.3036   -3.3261   49.0000 
+2774.8250    8.5000    8.6045   47.2714   65.4712    2.4793    0.0771   74.1893   -2.8434   49.0000 
+2774.9250    8.5000    8.6127   47.0179   67.5180    2.4894    0.0768   74.3913   -2.6525   49.0000 
+2775.0250    8.5000    8.5963   48.2087   69.2154    2.4685    0.0814   74.9510   -2.9146   49.0000 
+2775.1250    8.5000    8.5800   49.9834   69.7547    2.4282    0.0897   75.7551   -3.4455   49.0000 
+2775.2250    8.5000    8.6045   51.0206   69.6514    2.3931    0.0968   76.7643   -3.9110   49.0000 
+2775.3250    8.5000    8.6127   51.2126   69.9643    2.3794    0.1023   77.6888   -4.0022   49.0000 
+2775.4250    8.5000    8.6045   50.6287   70.5452    2.3806    0.1044   78.2418   -3.9087   49.0000 
+2775.5250    8.5000    8.5800   49.7145   70.5758    2.3863    0.1052   78.3439   -3.7659   49.0000 
+2775.6250    8.5000    8.5391   48.8771   69.2401    2.3901    0.1049   78.0286   -3.7020   49.0000 
+2775.7250    8.5000    8.5227   49.3534   67.3907    2.3915    0.1050   77.6403   -3.6700   49.0000 
+2775.8250    8.5000    8.5309   49.6915   66.3293    2.3882    0.1053   77.4056   -3.7273   49.0000 
+2775.9250    8.5000    8.5718   49.7760   66.3633    2.3875    0.1059   77.3679   -3.7191   49.0000 
+2776.0250    8.5000    8.5800   49.3073   67.5396    2.3882    0.1065   77.4776   -3.6868   49.0000 
+2776.1250    8.5000    8.5963   48.0243   69.2468    2.3925    0.1070   77.4821   -3.5855   49.0000 
+2776.2250    8.5000    8.6045   47.0025   71.5458    2.3846    0.1062   77.3418   -3.7663   49.0000 
+2776.3250    8.5000    8.6127   47.2637   73.9586    2.3769    0.1054   77.0520   -3.9489   49.0000 
+2776.4250    8.5000    8.6209   49.2689   74.9857    2.3666    0.1045   76.6847   -4.1841   49.0000 
+2776.5250    8.5000    8.6127   51.7965   73.4372    2.3691    0.1044   76.3316   -4.1390   49.0000 
+2776.6250    8.5000    8.5881   54.4854   70.3586    2.3704    0.1041   76.0745   -4.1229   49.0000 
+2776.7250    8.5000    8.5718   56.0681   67.8493    2.3739    0.1035   75.9413   -4.0725   49.0000 
+2776.8250    8.5000    8.5718   56.1910   66.8244    2.3736    0.1030   75.9020   -4.0961   49.0000 
+2776.9250    8.5000    8.5636   55.1615   66.6182    2.3769    0.1034   75.9077   -4.0143   49.0000 
+2777.0250    8.5000    8.5718   53.5405   66.7516    2.3795    0.1046   75.9199   -3.9231   49.0000 
+2777.1250    8.5000    8.5800   52.4956   67.1229    2.3772    0.1069   75.8811   -3.8936   49.0000 
+2777.2250    8.5000    8.5963   51.5891   68.3184    2.3697    0.1082   75.7561   -4.0005   49.0000 
+2777.3250    8.5000    8.6290   50.9284   70.4708    2.3615    0.1084   75.5112   -4.1559   49.0000 
+2777.4250    8.5000    8.6290   50.4136   73.7988    2.3574    0.1060   75.1388   -4.3173   49.0000 
+2777.5250    8.5000    8.6290   49.2996   77.9871    2.3554    0.1040   74.7801   -4.4246   49.0000 
+2777.6250    8.5000    8.6209   48.7158   82.0594    2.3579    0.1028   74.5128   -4.4153   49.0000 
+2777.7250    8.5000    8.6209   49.0231   84.4437    2.3645    0.1034   74.5179   -4.2639   49.0000 
+2777.8250    8.5000    8.6045   49.9988   83.6720    2.3779    0.1029   74.8714   -4.0113   49.0000 
+2777.9250    8.5000    8.5881   50.6672   80.9880    2.3871    0.1010   75.4362   -3.8908   49.0000 
+2778.0250    8.5000    8.5881   50.4213   78.1192    2.3911    0.0974   76.0464   -3.9322   49.0000 
+2778.1250    8.5000    8.5718   49.6992   76.5708    2.3869    0.0941   76.3097   -4.1246   49.0000 
+2778.2250    8.5000    8.5881   47.6863   76.3626    2.3879    0.0925   76.1862   -4.1573   49.0000 
+2778.3250    8.5000    8.5881   46.4033   76.6290    2.3919    0.0932   75.7821   -4.0538   49.0000 
+2778.4250    8.5000    8.5718   46.2727   77.5887    2.3984    0.0943   75.4577   -3.8885   49.0000 
+2778.5250    8.5000    8.5718   46.2112   78.5574    2.3986    0.0953   75.3827   -3.8507   49.0000 
+2778.6250    8.5000    8.5718   47.4097   79.5083    2.3945    0.0957   75.6173   -3.9210   49.0000 
+2778.7250    8.5000    8.5881   48.7388   79.3935    2.3846    0.0969   76.0765   -4.0765   49.0000 
+2778.8250    8.5000    8.5881   49.6300   78.6159    2.3738    0.0987   76.6173   -4.2343   49.0000 
+2778.9250    8.5000    8.5963   50.2907   77.8358    2.3667    0.1005   77.1275   -4.3156   49.0000 
+2779.0250    8.5000    8.6045   50.3061   77.1105    2.3653    0.1012   77.4332   -4.3226   49.0000 
+2779.1250    8.5000    8.6127   49.7606   76.4092    2.3699    0.1004   77.5332   -4.2559   49.0000 
+2779.2250    8.5000    8.6045   48.4776   75.3196    2.3743    0.0984   77.4240   -4.2352   49.0000 
+2779.3250    8.5000    8.5963   47.1255   74.4358    2.3800    0.0966   77.2944   -4.1798   49.0000 
+2779.4250    8.5000    8.5881   45.8962   73.6552    2.3818    0.0952   77.2117   -4.1894   49.0000 
+2779.5250    8.5000    8.5963   45.5582   72.3074    2.3846    0.0950   77.1689   -4.1416   49.0000 
+2779.6250    8.5000    8.5963   45.9731   69.8217    2.3871    0.0962   77.2097   -4.0534   49.0000 
+2779.7250    8.5000    8.5963   46.9027   66.5769    2.3876    0.0984   77.2102   -3.9678   49.0000 
+2779.8250    8.5000    8.5800   47.8476   64.1551    2.3803    0.1022   77.0306   -3.9865   49.0000 
+2779.9250    8.5000    8.5718   47.3790   62.9807    2.3624    0.1044   76.6582   -4.2711   49.0000 
+2780.0250    8.5000    8.5636   46.7183   62.3551    2.3459    0.1056   75.9796   -4.5624   49.0000 
+2780.1250    8.5000    8.5472   46.4724   61.0726    2.3389    0.1032   75.2602   -4.7816   49.0000 
+2780.2250    8.5000    8.5636   47.6940   58.9353    2.3493    0.1013   74.5755   -4.6370   49.0000 
+2780.3250    8.5000    8.5718   50.9975   56.6129    2.3724    0.1003   74.0347   -4.2102   49.0000 
+2780.4250    8.5000    8.6045   55.1846   54.3392    2.4017    0.1030   73.8224   -3.5309   49.0000 
+2780.5250    8.5000    8.6209   58.2269   52.1600    2.4302    0.1093   73.9862   -2.7532   49.0000 
+2780.6250    8.5000    8.5963   58.8876   50.8008    2.4527    0.1169   74.4531   -2.0509   49.0000 
+2780.7250    8.5000    8.5963   56.6059   51.0592    2.4590    0.1221   75.2418   -1.7475   49.0000 
+2780.8250    8.5000    8.5800   52.3804   53.4831    2.4479    0.1217   76.0265   -1.9858   49.0000 
+2780.9250    8.5000    8.5718   49.1153   57.1296    2.4166    0.1179   76.6821   -2.7389   49.0000 
+2781.0250    8.5000    8.6045   46.4724   60.8910    2.3895    0.1136   77.1270   -3.4227   49.0000 
+2781.1250    8.5000    8.5881   45.8885   63.7390    2.3697    0.1123   77.3556   -3.8627   49.0000 
+2781.2250    8.5000    8.5881   46.6414   66.1623    2.3604    0.1125   77.6327   -4.0410   49.0000 
+2781.3250    8.5000    8.5881   47.0486   67.8838    2.3481    0.1135   77.9913   -4.2543   49.0000 
+2781.4250    8.5000    8.5800   47.6940   68.6888    2.3352    0.1142   78.3857   -4.4896   49.0000 
+2781.5250    8.5000    8.5800   48.1242   68.4046    2.3262    0.1152   78.5832   -4.6380   49.0000 
+2781.6250    8.5000    8.5800   49.4763   67.9046    2.3244    0.1159   78.5577   -4.6487   49.0000 
+2781.7250    8.5000    8.5718   50.6211   67.6928    2.3315    0.1155   78.4362   -4.5204   49.0000 
+2781.8250    8.5000    8.5963   52.5878   67.8479    2.3410    0.1131   78.5128   -4.4098   49.0000 
+2781.9250    8.5000    8.6209   54.8849   68.1748    2.3518    0.1101   78.8500   -4.2950   49.0000 
+2782.0250    8.5000    8.6372   55.6225   68.9742    2.3573    0.1075   79.1781   -4.2726   49.0000 
+2782.1250    8.5000    8.6290   55.7685   71.2411    2.3667    0.1066   79.3214   -4.1137   49.0000 
+2782.2250    8.5000    8.5881   54.5546   76.0307    2.3747    0.1064   79.1301   -3.9591   49.0000 
+2782.3250    8.5000    8.5881   51.3356   83.0038    2.3829    0.1058   78.7857   -3.8168   49.0000 
+2782.4250    8.5000    8.5881   47.4020   89.3718    2.3836    0.1041   78.4163   -3.8563   49.0000 
+2782.5250    8.5000    8.6127   43.5761   92.6735    2.3828    0.1014   78.0194   -3.9631   49.0000 
+2782.6250    8.5000    8.6209   39.8039   94.2774    2.3810    0.0993   77.5638   -4.0707   49.0000 
+2782.7250    8.5000    8.6454   38.0292   97.4139    2.3767    0.0976   76.9480   -4.2136   49.0000 
+2782.8250    8.5000    8.6536   37.7757  101.7457    2.3686    0.0964   76.2612   -4.4135   49.0000 
+2782.9250    8.5000    8.6618   37.8294  106.0008    2.3599    0.0956   75.5939   -4.6135   49.0000 
+2783.0250    8.5000    8.6372   39.1278  108.0418    2.3567    0.0938   75.0168   -4.7405   49.0000 
+2783.1250    8.5000    8.6290   40.6567  107.2573    2.3600    0.0916   74.6199   -4.7465   49.0000 
+2783.2250    8.5000    8.5963   42.6541  104.2338    2.3630    0.0879   74.3770   -4.8104   49.0000 
+2783.3250    8.5000    8.5881   46.4263   97.7115    2.3680    0.0856   74.4005   -4.7853   49.0000 
+2783.4250    8.5000    8.6290   50.7517   88.5578    2.3734    0.0843   74.6811   -4.7230   49.0000 
+2783.5250    8.5000    8.6372   54.7467   77.5772    2.3872    0.0861   75.1372   -4.3860   49.0000 
+2783.6250    8.5000    8.6781   58.9183   67.4741    2.4010    0.0894   75.6434   -4.0019   49.0000 
+2783.7250    8.5000    8.6781   61.9530   59.7026    2.4145    0.0943   76.1403   -3.5663   49.0000 
+2783.8250    8.5000    8.6454   63.3205   54.2731    2.4248    0.0986   76.5464   -3.2173   49.0000 
+2783.9250    8.5000    8.6781   63.4818   51.2682    2.4311    0.1025   76.7689   -2.9605   49.0000 
+2784.0250    8.5000    8.6536   61.2769   49.9893    2.4345    0.1053   76.6607   -2.7988   49.0000 
+2784.1250    8.5000    8.6781   57.4586   50.2999    2.4285    0.1065   76.1199   -2.8811   49.0000 
+2784.2250    8.5000    8.6781   53.1871   51.8046    2.4220    0.1053   75.2577   -3.0490   49.0000 
+2784.3250    8.5000    8.6454   49.4303   54.8855    2.4152    0.1018   74.2852   -3.3035   49.0000 
+2784.4250    8.5000    8.6454   46.5723   60.2093    2.4127    0.0978   73.4847   -3.4854   49.0000 
+2784.5250    8.5000    8.6372   45.6427   67.2466    2.4089    0.0936   73.1122   -3.7010   49.0000 
+2784.6250    8.5000    8.6454   46.0883   74.4421    2.4030    0.0905   73.2265   -3.9236   49.0000 
+2784.7250    8.5000    8.6618   47.4558   78.7836    2.3980    0.0878   73.7270   -4.1151   49.0000 
+2784.8250    8.5000    8.6699   49.5301   79.1687    2.3973    0.0870   74.3526   -4.1530   49.0000 
+2784.9250    8.5000    8.6699   50.4060   75.2424    2.3991    0.0872   74.9679   -4.1116   49.0000 
+2785.0250    8.5000    8.6536   50.9437   68.3769    2.4008    0.0906   75.5025   -3.9632   49.0000 
+2785.1250    8.5000    8.6781   50.4828   60.5441    2.3974    0.0949   76.1454   -3.8878   49.0000 
+2785.2250    8.5000    8.6536   50.1985   53.1923    2.3921    0.1017   76.8327   -3.7673   49.0000 
+2785.3250    8.5000    8.6454   50.8285   47.2988    2.3902    0.1066   77.4480   -3.6414   49.0000 
+2785.4250    8.5000    8.6781   51.3817   42.8767    2.3888    0.1115   77.8903   -3.5071   49.0000 
+2785.5250    8.5000    8.7027   52.3343   39.9485    2.3859    0.1137   78.0689   -3.4929   49.0000 
+2785.6250    8.5000    8.6945   52.9489   38.1850    2.3756    0.1145   78.1408   -3.6717   49.0000 
+2785.7250    8.5000    8.6863   53.4406   37.3163    2.3713    0.1138   78.1418   -3.7816   49.0000 
+2785.8250    8.5000    8.6618   54.0706   36.8182    2.3731    0.1137   78.1439   -3.7483   49.0000 
+2785.9250    8.5000    8.6372   55.6302   36.3628    2.3779    0.1147   78.1148   -3.6202   49.0000 
+2786.0250    8.5000    8.6618   57.9042   35.8746    2.3750    0.1158   78.0168   -3.6404   49.0000 
+2786.1250    8.5000    8.6863   60.0246   35.5802    2.3694    0.1163   77.8699   -3.7363   49.0000 
+2786.2250    8.5000    8.6699   62.4063   35.5263    2.3729    0.1161   77.5975   -3.6726   49.0000 
+2786.3250    8.5000    8.6618   63.5664   35.5337    2.3905    0.1148   77.2592   -3.3621   49.0000 
+2786.4250    8.5000    8.6372   63.3128   35.4713    2.4162    0.1127   76.8153   -2.9197   49.0000 
+2786.5250    8.5000    8.6536   62.3986   35.4190    2.4420    0.1098   76.4194   -2.4981   49.0000 
+2786.6250    8.5000    8.6454   60.5240   35.6315    2.4537    0.1073   76.1408   -2.3471   49.0000 
+2786.7250    8.5000    8.6781   58.7263   36.0634    2.4495    0.1048   76.0245   -2.5161   49.0000 
+2786.8250    8.5000    8.7108   57.4817   36.5726    2.4291    0.1046   76.1684   -2.9306   49.0000 
+2786.9250    8.5000    8.6781   56.9285   36.8593    2.4127    0.1061   76.6173   -3.2107   49.0000 
+2787.0250    8.5000    8.6699   56.6673   36.9043    2.4054    0.1108   77.3929   -3.1992   49.0000 
+2787.1250    8.5000    8.6781   56.9669   36.6635    2.4023    0.1153   78.3725   -3.1110   49.0000 
+2787.2250    8.5000    8.6536   57.4433   36.3010    2.3951    0.1200   79.2194   -3.0991   49.0000 
+2787.3250    8.5000    8.6863   56.6981   35.8844    2.3841    0.1222   79.6551   -3.2446   49.0000 
+2787.4250    8.5000    8.6618   56.6097   35.6124    2.3787    0.1225   79.5270   -3.3445   49.0000 
+2787.5250    8.5000    8.6781   55.3036   35.4848    2.3818    0.1198   78.9653   -3.3703   49.0000 
+2787.6250    8.5000    8.6781   53.5712   35.5321    2.3870    0.1167   78.1337   -3.3699   49.0000 
+2787.7250    8.5000    8.6863   54.0475   35.6339    2.3880    0.1143   77.3939   -3.4288   49.0000 
+2787.8250    8.5000    8.7272   53.5251   35.7311    2.3790    0.1141   77.0786   -3.6164   49.0000 
+2787.9250    8.5000    8.7027   53.9400   35.6852    2.3677    0.1146   77.2388   -3.8240   49.0000 
+2788.0250    8.5000    8.6863   54.7159   35.4010    2.3601    0.1151   78.0184   -3.9602   49.0000 
+2788.1250    8.5000    8.6781   54.2857   34.7745    2.3598    0.1158   78.9750   -3.9446   49.0000 
+2788.2250    8.5000    8.6863   54.9042   33.9511    2.3635    0.1156   79.6949   -3.8752   49.0000 
+2788.3250    8.5000    8.6699   56.1026   33.1982    2.3676    0.1153   80.0153   -3.8054   49.0000 
+2788.4250    8.5000    8.6699   57.4894   32.8064    2.3724    0.1133   79.7582   -3.7750   49.0000 
+2788.5250    8.5000    8.6045   58.6264   32.7828    2.3799    0.1130   79.2510   -3.6365   49.0000 
+2788.6250    8.5000    8.6209   59.7711   32.9752    2.3889    0.1120   78.6204   -3.4876   49.0000 
+2788.7250    8.5000    8.6618   61.0311   33.0919    2.4023    0.1103   77.8255   -3.2761   49.0000 
+2788.8250    8.5000    8.6536   63.5664   32.8020    2.4138    0.1057   77.0306   -3.1995   49.0000 
+2788.9250    8.5000    8.6372   67.3309   31.7999    2.4253    0.1024   76.1704   -3.0799   49.0000 
+2789.0250    8.5000    8.6045   70.7881   30.1522    2.4309    0.1028   75.5714   -2.9564   49.0000 
+2789.1250    8.5000    8.6372   72.6626   28.2439    2.4418    0.1095   75.4551   -2.5127   49.0000 
+2789.2250    8.5000    8.6372   71.8636   26.4831    2.4586    0.1188   75.8480   -1.8668   49.0000 
+2789.3250    8.5000    8.6536   69.6818   25.1659    2.4724    0.1271   76.7464   -1.3151   49.0000 
+2789.4250    8.5000    8.6699   66.1477   24.2530    2.4683    0.1300   77.6934   -1.3008   49.0000 
+2789.5250    8.5000    8.6372   62.3064   23.6836    2.4446    0.1295   78.2240   -1.7908   49.0000 
+2789.6250    8.5000    8.6290   59.1104   23.3560    2.4241    0.1281   78.0985   -2.2478   49.0000 
+2789.7250    8.5000    8.6209   56.3293   23.2790    2.4158    0.1272   77.8179   -2.4452   49.0000 
+2789.8250    8.5000    8.6045   55.4919   23.4347    2.4191    0.1251   77.6709   -2.4483   49.0000 
+2789.9250    8.5000    8.5963   56.3984   23.8293    2.4216    0.1205   78.0332   -2.5513   49.0000 
+2790.0250    8.5000    8.6209   57.7045   24.3800    2.4186    0.1142   78.3985   -2.8209   49.0000 
+2790.1250    8.5000    8.6372   58.4574   25.0489    2.4153    0.1086   78.2393   -3.0739   49.0000 
+2790.2250    8.5000    8.6454   57.5201   25.8789    2.4126    0.1042   77.5852   -3.2760   49.0000 
+2790.3250    8.5000    8.6945   55.5764   26.9612    2.4096    0.1003   76.6689   -3.4659   49.0000 
+2790.4250    8.5000    8.6863   53.1333   28.3123    2.4077    0.0964   75.9337   -3.6335   49.0000 
+2790.5250    8.5000    8.6454   51.7197   29.8423    2.4054    0.0938   75.4862   -3.7660   49.0000 
+2790.6250    8.5000    8.6454   51.2664   31.5418    2.4126    0.0931   75.1275   -3.6466   49.0000 
+2790.7250    8.5000    8.6290   51.2818   33.4291    2.4196    0.0929   74.6974   -3.5123   49.0000 
+2790.8250    8.5000    8.6454   52.6339   35.4558    2.4236    0.0922   74.2668   -3.4531   49.0000 
+2790.9250    8.5000    8.6536   52.6954   37.2943    2.4204    0.0918   73.9985   -3.5313   49.0000 
+2791.0250    8.5000    8.6536   52.6608   38.4712    2.4112    0.0929   73.9776   -3.6797   49.0000 
+2791.1250    8.5000    8.6536   52.8836   38.6200    2.4059    0.0941   74.3077   -3.7445   49.0000 
+2791.2250    8.5000    8.6372   53.0526   37.5372    2.4005    0.0946   74.8051   -3.8387   49.0000 
+2791.3250    8.5000    8.6618   55.4804   35.5901    2.4030    0.0934   74.9036   -3.8278   49.0000 
+2791.4250    8.5000    8.6863   59.8057   33.2859    2.4113    0.0923   74.4827   -3.6978   49.0000 
+2791.5250    8.5000    8.7190   65.1989   31.2241    2.4358    0.0908   73.3837   -3.2581   49.0000 
+2791.6250    8.5000    8.6699   70.9148   29.8006    2.4734    0.0898   72.0092   -2.5372   49.0000 
+2791.7250    8.5000    8.6618   75.7088   29.0777    2.5173    0.0886   71.1755   -1.7019   49.0000 
+2791.8250    8.5000    8.6781   78.3708   28.9191    2.5458    0.0886   70.9102   -1.1299   49.0000 
+2791.9250    8.5000    8.6699   78.5552   29.0818    2.5494    0.0892   71.2429   -1.0400   49.0000 
+2792.0250    8.5000    8.6618   75.5283   29.5596    2.5314    0.0912   71.6781   -1.3332   49.0000 
+2792.1250    8.5000    8.6945   70.1120   30.5581    2.5081    0.0947   72.1551   -1.6816   49.0000 
+2792.2250    8.5000    8.6618   64.0119   32.1166    2.4838    0.0987   72.7454   -2.0329   49.0000 
+2792.3250    8.5000    8.6699   57.9350   34.0238    2.4616    0.1008   73.3985   -2.4081   49.0000 
+2792.4250    8.5000    8.6945   54.5392   35.8445    2.4396    0.0988   73.9709   -2.9153   49.0000 
+2792.5250    8.5000    8.6781   53.6173   37.3383    2.4289    0.0947   74.2679   -3.2675   49.0000 
+2792.6250    8.5000    8.6699   53.8555   38.4757    2.4222    0.0915   74.5066   -3.5068   49.0000 
+2792.7250    8.5000    8.6536   54.8926   39.2549    2.4192    0.0915   74.8163   -3.5645   49.0000 
+2792.8250    8.5000    8.6209   54.9387   39.7650    2.4090    0.0938   75.1918   -3.6932   49.0000 
+2792.9250    8.5000    8.5881   54.6929   40.3053    2.4020    0.0969   75.3781   -3.7313   49.0000 
+2793.0250    8.5000    8.5881   53.5712   41.2459    2.4017    0.0989   75.0995   -3.6692   49.0000 
+2793.1250    8.5000    8.6290   51.9348   42.6428    2.4101    0.0993   74.5735   -3.4879   49.0000 
+2793.2250    8.5000    8.6290   50.9822   43.8412    2.4159    0.0979   74.1225   -3.4181   49.0000 
+2793.3250    8.5000    8.6454   49.0769   44.1391    2.4124    0.0966   74.1020   -3.5302   49.0000 
+2793.4250    8.5000    8.6536   47.6095   43.3745    2.4025    0.0974   74.5510   -3.7034   49.0000 
+2793.5250    8.5000    8.6290   47.6018   42.2743    2.3947    0.1010   75.2398   -3.7382   49.0000 
+2793.6250    8.5000    8.6945   47.5250   41.2606    2.3934    0.1049   75.8673   -3.6362   49.0000 
+2793.7250    8.5000    8.7354   48.3470   40.2987    2.3951    0.1078   76.3214   -3.5044   49.0000 
+2793.8250    8.5000    8.7517   49.3457   39.0610    2.3956    0.1090   76.4949   -3.4559   49.0000 
+2793.9250    8.5000    8.7436   50.1563   37.9115    2.3944    0.1090   76.1480   -3.4785   49.0000 
+2794.0250    8.5000    8.6945   50.4789   37.3845    2.3964    0.1073   75.3775   -3.4967   49.0000 
+2794.1250    8.5000    8.6863   50.7401   37.6493    2.3970    0.1043   74.3673   -3.5817   49.0000 
+2794.2250    8.5000    8.6863   51.2088   38.3746    2.3957    0.1011   73.5306   -3.7146   49.0000 
+2794.3250    8.5000    8.7027   50.0026   38.8437    2.3900    0.0980   73.3418   -3.9316   49.0000 
+2794.4250    8.5000    8.7354   49.4879   38.7815    2.3900    0.0965   73.6704   -3.9820   49.0000 
+2794.5250    8.5000    8.7272   48.3201   38.3626    2.3903    0.0963   74.4990   -3.9833   49.0000 
+2794.6250    8.5000    8.7517   47.2753   38.0618    2.3887    0.0987   75.4658   -3.9363   49.0000 
+2794.7250    8.5000    8.7354   48.4776   37.9924    2.3798    0.1009   76.1413   -4.0400   49.0000 
+2794.8250    8.5000    8.6699   49.7068   38.1723    2.3733    0.1033   76.3444   -4.0899   49.0000 
+2794.9250    8.5000    8.6699   51.6582   38.6641    2.3742    0.1035   76.1148   -4.0667   49.0000 
+2795.0250    8.5000    8.6372   53.7325   39.2876    2.3831    0.1033   75.7128   -3.8948   49.0000 
+2795.1250    8.5000    8.6536   54.4701   39.3385    2.3975    0.1025   75.5189   -3.6340   49.0000 
+2795.2250    8.5000    8.6699   55.8837   37.8135    2.4052    0.1031   75.6260   -3.4584   49.0000 
+2795.3250    8.5000    8.6945   58.9414   35.0487    2.4071    0.1038   75.9362   -3.3979   49.0000 
+2795.4250    8.5000    8.7108   62.3218   32.1318    2.4016    0.1051   76.1791   -3.4649   49.0000 
+2795.5250    8.5000    8.7108   65.6484   29.9484    2.4059    0.1081   76.2648   -3.2796   49.0000 
+2795.6250    8.5000    8.7108   66.9390   28.6670    2.4168    0.1126   76.0204   -2.9107   49.0000 
+2795.7250    8.5000    8.6781   64.7264   28.2619    2.4301    0.1158   75.4306   -2.5399   49.0000 
+2795.8250    8.5000    8.6945   60.4856   28.7324    2.4331    0.1137   74.5520   -2.5471   49.0000 
+2795.9250    8.5000    8.6618   56.6443   30.0204    2.4313    0.1067   73.5714   -2.8181   49.0000 
+2796.0250    8.5000    8.6536   53.3023   32.0355    2.4274    0.0975   72.8163   -3.2035   49.0000 
+2796.1250    8.5000    8.6699   50.9668   34.5034    2.4301    0.0883   72.5275   -3.4559   49.0000 
+2796.2250    8.5000    8.6618   49.8298   37.3064    2.4324    0.0814   72.5112   -3.6388   49.0000 
+2796.3250    8.5000    8.6945   48.8156   40.2895    2.4394    0.0779   72.7857   -3.6172   49.0000 
+2796.4250    8.5000    8.7272   49.3381   43.3685    2.4382    0.0787   73.1204   -3.6118   49.0000 
+2796.5250    8.5000    8.7354   51.0667   45.8683    2.4332    0.0824   73.4847   -3.5884   49.0000 
+2796.6250    8.5000    8.7517   54.4317   46.7475    2.4199    0.0871   73.9214   -3.6990   49.0000 
+2796.7250    8.5000    8.7272   58.0886   45.5960    2.4132    0.0920   74.4138   -3.6680   49.0000 
+2796.8250    8.5000    8.6945   60.5701   43.0328    2.4174    0.0964   75.0505   -3.4405   49.0000 
+2796.9250    8.5000    8.6781   62.2142   40.3141    2.4314    0.1010   75.7168   -3.0059   49.0000 
+2797.0250    8.5000    8.6945   60.9005   37.9872    2.4401    0.1047   76.3046   -2.7084   49.0000 
+2797.1250    8.5000    8.6699   58.1040   36.5081    2.4367    0.1074   76.7464   -2.6877   49.0000 
+2797.2250    8.5000    8.6699   54.5546   35.8270    2.4177    0.1077   76.9872   -3.0571   49.0000 
+2797.3250    8.5000    8.6290   51.2126   35.9161    2.3973    0.1068   77.1097   -3.4945   49.0000 
+2797.4250    8.5000    8.6290   49.5685   36.4302    2.3831    0.1050   76.9648   -3.8385   49.0000 
+2797.5250    8.5000    8.6372   48.8617   37.2244    2.3828    0.1033   76.6097   -3.9002   49.0000 
+2797.6250    8.5000    8.6290   49.2075   38.0804    2.3892    0.1015   76.0291   -3.8329   49.0000 
+2797.7250    8.5000    8.6781   49.6684   38.8278    2.3960    0.0992   75.3408   -3.7718   49.0000 
+2797.8250    8.5000    8.6618   50.8285   39.2123    2.3997    0.0971   74.7929   -3.7709   49.0000 
+2797.9250    8.5000    8.6699   53.4483   39.1157    2.4052    0.0954   74.5112   -3.7156   49.0000 
+2798.0250    8.5000    8.6699   56.5905   38.4498    2.4112    0.0958   74.6061   -3.5820   49.0000 
+2798.1250    8.5000    8.6618   59.1104   37.2747    2.4191    0.0981   74.9755   -3.3463   49.0000 
+2798.2250    8.5000    8.6863   59.0950   35.8924    2.4215    0.1024   75.4592   -3.1540   49.0000 
+2798.3250    8.5000    8.6863   56.0066   34.6375    2.4201    0.1080   75.8704   -2.9979   49.0000 
+2798.4250    8.5000    8.6372   51.9348   33.9048    2.4131    0.1122   76.0990   -2.9963   49.0000 
+2798.5250    8.5000    8.6536   48.8310   33.8908    2.4075    0.1135   76.1531   -3.0661   49.0000 
+2798.6250    8.5000    8.6618   48.2779   34.7616    2.4043    0.1101   76.0194   -3.2442   49.0000 
+2798.7250    8.5000    8.6863   49.5609   36.3306    2.4065    0.1045   75.7041   -3.3878   49.0000 
+2798.8250    8.5000    8.7272   51.4277   38.2230    2.4074    0.0983   75.3765   -3.5761   49.0000 
+2798.9250    8.5000    8.6781   53.2409   40.0301    2.4130    0.0942   75.0153   -3.5991   49.0000 
+2799.0250    8.5000    8.6781   54.1167   41.5060    2.4152    0.0926   74.8571   -3.6096   49.0000 
+2799.1250    8.5000    8.6618   55.5610   42.4623    2.4167    0.0931   74.9541   -3.5622   49.0000 
+2799.2250    8.5000    8.6781   57.7122   42.7581    2.4085    0.0948   75.1857   -3.6690   49.0000 
+2799.3250    8.5000    8.7027   59.4331   42.1961    2.4010    0.0967   75.5653   -3.7572   49.0000 
+2799.4250    8.5000    8.6699   61.1386   40.8992    2.3988    0.0982   75.9577   -3.7503   49.0000 
+2799.5250    8.5000    8.6290   61.2769   39.0710    2.4030    0.1006   76.4097   -3.5853   49.0000 
+2799.6250    8.5000    8.6454   58.8185   37.2788    2.4074    0.1037   76.9434   -3.3944   49.0000 
+2799.7250    8.5000    8.6290   56.3139   35.8670    2.4041    0.1084   77.4699   -3.3037   49.0000 
+2799.8250    8.5000    8.6699   53.2946   35.1357    2.4004    0.1121   77.8515   -3.2545   49.0000 
+2799.9250    8.5000    8.6699   50.9284   35.0069    2.3962    0.1152   78.0413   -3.2362   49.0000 
diff --git a/examples/basic_flow.py b/examples/basic_flow.py
index f8a1f53..438668d 100644
--- a/examples/basic_flow.py
+++ b/examples/basic_flow.py
@@ -9,13 +9,12 @@
 """
 
 from cProfile import label
-import las2 # local las2 read
 import numpy as np
 import matplotlib.pyplot as plt
 import numpy.typing as npt
 
-#from stoneforge.petrophysics import porosity
 
+from stoneforge.preprocessing import las2
 well = las2.read('../datasets/DP1.las')
 #well = las2.read('7-MP-22-BA.las')
 DP1_DATA = {} # data information from DP1 welllog
@@ -143,8 +142,8 @@
 
 # %%
 
-import porosity
-import shale_volume
+from stoneforge.petrophysics import porosity
+from stoneforge.petrophysics import shale_volume
 
 PHID = porosity.porosity("density", rhob = RHOB_C, rhom = 2.65, rhof = 1.10)
 VSH = shale_volume.vshale(gr = well_DP1_c["GR"]["data"], grmin = 0.0, grmax = 150.0, method = "linear")
@@ -165,10 +164,6 @@
 PHIT = porosity.porosity(method = "sonic", dt = well_DP1["DT"]["data"], dtma = 55.5, dtf = 185)
 print(PHIT)
 
-# %%
-
-
-
 # %%
 
 fig, ax = plt.subplots(1, 3)
@@ -198,7 +193,8 @@
 ax[2].grid()
 
 # %%
+from stoneforge.petrophysics import water_saturation
 
+# %%
 
-
-# %%
\ No newline at end of file
+sw = water_saturation.archie()
\ No newline at end of file
diff --git a/examples/data_loading.py b/examples/data_loading.py
index dce8ce5..ac3b899 100644
--- a/examples/data_loading.py
+++ b/examples/data_loading.py
@@ -6,8 +6,7 @@
 
 A tutorial exercise about loading well log datasets
 """
-
-import las2 # local las2 read
+from stoneforge.preprocessing import las2
 import numpy as np
 import matplotlib.pyplot as plt
 
diff --git a/examples/las2.py b/examples/las2.py
deleted file mode 100644
index 463aa7e..0000000
--- a/examples/las2.py
+++ /dev/null
@@ -1,373 +0,0 @@
-import re
-import numpy as np
-import io
-
-
-class LAS2Error(Exception):
-    pass
-
-
-_default_line_format_format = (
-    "{{mnemonic:<{mnemonic}}}."
-    "{{unit:<{unit}}} "
-    "{{value:<{value}}} : "
-    "{{description:<{description}}}"
-)
-
-_default_cell_format = "{:<8.4f}"
-
-_line_regex = re.compile(
-    r"(?P<mnemonic>[^\.]+)\.(?P<unit>\S*)(?P<value>.*):(?P<description>.*)"
-)
-
-print(_line_regex)
-
-_line_elements = ["mnemonic", "unit", "value", "description"]
-
-_sections = {
-    "V": "version",
-    "W": "well",
-    "P": "parameter",
-    "C": "curve",
-    "O": "other",
-    "A": "data",
-}
-
-_sections_order = ["version", "well", "parameter", "curve", "other", "data"]
-
-
-def _get_null_value(sections):
-    nullstring = None
-    for line in sections["well"]:
-        if line["mnemonic"] == "NULL":
-            nullstring = line["value"]
-            break
-    return float(nullstring)
-
-
-def _parse_line(line):
-    match = _line_regex.match(line)
-
-    if match is None:
-        raise LAS2Error("'{}' is not a valid LAS 2.0 line.".format(line))
-
-    parsed_lines = {k: v.strip() for k, v in match.groupdict().items()}
-    #parsed_lines.replace(/[^a-zA-Z0-9 ]/g, "")
-    #print(parsed_lines)
-
-    return parsed_lines
-
-
-def _parse_section(lines, previous_sections):
-    return [_parse_line(line) for line in lines]
-
-
-def _parse_plain_text_section(lines, previous_sections):
-    return lines
-
-
-def _parse_data_section(lines, previous_sections):
-    ncols = len(previous_sections["curve"])
-    nullvalue = _get_null_value(previous_sections)
-
-    data = np.array(" ".join(lines).split(), dtype=float)
-    data[data == nullvalue] = np.nan
-    data = data.reshape((-1, ncols)).transpose()
-
-    return data
-
-
-_parsers = {
-    "version": _parse_section,
-    "well": _parse_section,
-    "parameter": _parse_section,
-    "curve": _parse_section,
-    "other": _parse_plain_text_section,
-    "data": _parse_data_section,
-}
-
-
-def read(lasfile):
-    """Reads the contents of a LAS 2.0 file.
-
-    Parameters
-    ----------
-    lasfile : string or file-like object
-        The path of the file to read or an existing file-like object to read from.
-
-    Returns
-    -------
-    dict
-        A dictionary containing the sections of the LAS file.
-
-    Notes
-    -----
-    The structure of the returned dictionary is specified below.
-    The dictionary keys are the section names: 'version', 'well', 'parameter', 'curve', 'other', 'data'.
-    Not all sections must be present on a LAS 2.0 file.
-    For more information on the contents of each section, please refer to the LAS 2.0 standard [1]_.
-
-    The value of the 'data' section is a numpy ndarray where each row contains the data for a well log.
-
-    The value of the 'other' section is a list of lines exactly as found on the original file.
-
-    For all other sections, the values are dictionaries containing four keys: 'mnemonic', 'unit', 'value' and
-    'description'.
-    For information on the structure of a LAS 2.0 line, please also refer to its specification [1]_.
-
-    References
-    ----------
-    .. [1] LAS 2.0 standard - http://www.cwls.org/wp-content/uploads/2017/02/Las2_Update_Feb2017.pdf -
-       Retrieved August 14, 2019
-
-    Examples
-    --------
-    The examples below contains ficticious data.
-    In the first example we see the version information for the file.
-    >>> import las2
-    >>> lasfile = las2.read('path/to/the/las/file')
-    >>> lasfile['version'][0]
-    {'mnemonic': 'VERS', 'unit': '', 'value': '2.00', 'description': 'CWLS LOG ASCII STANDARD - VERSION 2.00'}
-
-    Here we print the names and units for each of the well logs (note that 'DEPTH' is read as a well log).
-    >>> for curve_info in lasfile['curve']:
-    ...     print("{mnemonic} ({unit})".format(**curve_info))
-    DEPTH (M)
-    GR (API)
-    ...
-
-    The data section where each row contains the values for a log (first row is depth, second is GR, etc...)
-    >>> lasfile['data']
-    array([[1000.0, 1000.2, ..., 1100.0],
-           [25.0,     26.0, ...,   75.0],
-           ...]])
-    """
-    sections = {}
-    current_section_key = ""
-    current_section = []
-
-    if isinstance(lasfile, io.IOBase):
-        lasfile.seek(0)
-        close_file = False
-    else:
-        lasfile = open(lasfile, "r")
-        close_file = True
-
-    for line in lasfile:
-        if line.lstrip().startswith("#"):
-            continue
-        elif line.lstrip().startswith("~"):
-            _, section_title = line.split("~", 1)
-            sections[current_section_key] = current_section
-            current_section_key = _sections[section_title[0].upper()]
-            current_section = []
-        else:
-            current_section.append(line)
-    sections[current_section_key] = current_section
-
-    if close_file:
-        lasfile.close()
-
-    del sections[""]
-
-    parsed_sections = {}
-
-    for section_key in sections:
-        parser = _parsers[section_key]
-        section = sections[section_key]
-        parsed_sections[section_key] = parser(section, parsed_sections)
-
-    return parsed_sections
-
-
-def _compose_line(line, format):
-    return format.format(**line)
-
-
-def _compose_section(lines, format, previous_sections):
-    return [_compose_line(line, format).rstrip() for line in lines]
-
-
-def _compose_plain_text_section(lines, format, previous_sections):
-    return lines
-
-
-def _compose_data_section(data, format, previous_sections):
-    nullvalue = _get_null_value(previous_sections)
-
-    data_section = []
-    for i in range(data.shape[1]):
-        nanfreeline = data[:, i]
-        nanfreeline[np.isnan(nanfreeline)] = nullvalue
-        data_section.append(format.format(*nanfreeline).rstrip())
-
-    return data_section
-
-
-_composers = {
-    "version": _compose_section,
-    "well": _compose_section,
-    "parameter": _compose_section,
-    "curve": _compose_section,
-    "other": _compose_plain_text_section,
-    "data": _compose_data_section,
-}
-
-
-def _section_title_getter(key, section):
-    return "~" + key.upper()
-
-
-def _data_title_getter(key, section):
-    return "~A"
-
-
-_default_section_title_getters = {
-    "version": _section_title_getter,
-    "well": _section_title_getter,
-    "parameter": _section_title_getter,
-    "curve": _section_title_getter,
-    "other": _section_title_getter,
-    "data": _data_title_getter,
-}
-
-
-def _section_format_getter(section):
-    maxwidths = dict.fromkeys(_line_elements, 0)
-    for line in section:
-        for key in line:
-            if len(line[key]) > maxwidths[key]:
-                maxwidths[key] = len(line[key])
-
-    return _default_line_format_format.format(**maxwidths)
-
-
-def _plain_text_format_getter(section):
-    return "{}"
-
-
-def _data_format_getter(section):
-    n = section.shape[0]
-    return " ".join([_default_cell_format] * n)
-
-
-_default_section_format_getters = {
-    "version": _section_format_getter,
-    "well": _section_format_getter,
-    "parameter": _section_format_getter,
-    "curve": _section_format_getter,
-    "other": _plain_text_format_getter,
-    "data": _data_format_getter,
-}
-
-
-def write(lasfile, data, section_titles=None, section_formats=None):
-    """Writes well log data to a file using the LAS 2.0 format.
-
-    Parameters
-    ----------
-    lasfile : string or file-like object
-        The path of the file to read or an existing file-like object to read from.
-    data : dict
-        A dictionary with the same structure as returned by the `read` function.
-    section_titles : dict, optional
-        A dictionary where the key is the section name and value is the title that will be used at the beggining
-        of the LAS 2.0 file section. For further information please refer to the Notes section.
-    section_formats : dict, optional
-        A dictionary where the key is the section name and value is the format string that will be used to format the
-        lines in the respective section. For further information please refer to the Notes section.
-
-    Notes
-    -----
-    This function does not guarantee that the output file will follow the LAS 2.0 standard. If mandatory sections or
-    lines are missing from the inputs, the file will be written nevertheless. The only required field for the function
-    work is the 'NULL' value in the 'well' section.
-    Also, no checks are made to guarantee the validity of section titles or formats.
-
-    Possible section names are: 'version', 'well', 'parameter', 'curve', 'other', 'data'.
-
-    Default section titles are '~' followed by the section name (for instance '~VERSION', for the 'version' section),
-    except for the 'data' section, which defaults to '~A'.
-    Each section title can be individually omitted.
-    For more information on the rules for section titles, please refer to the LAS 2.0 standard [1]_.
-
-    Format strings for 'version', 'well', 'parameter' and 'curve' must contain the following fields: 'mnemonic', 'unit',
-    'value' and 'description'. Here is an example of a valid format: "{mnemonic}.{unit} {value} : {description}". The
-    default format left align fields in the same section within columns with the same width.
-    For more information on the construction of valid LAS 2.0 lines, please refer to the LAS 2.0 standard [1]_.
-    For the 'other' section, the format string is simply the format of each line of this section. For example, "{}"
-    will output the lines as is, which is the default value for this section.
-    The format string for the 'data' section contains a column for each well log. For example, in the case of 3 well
-    logs, "{:>8.4f} {:>8.4f} {:>8.4f}" is the default format.
-    Each section format can be individually omitted.
-
-    See Also
-    --------
-    read : Reads the contents of a LAS 2.0 file.
-
-    References
-    ----------
-    .. [1] LAS 2.0 standard - http://www.cwls.org/wp-content/uploads/2017/02/Las2_Update_Feb2017.pdf -
-       Retrieved August 14, 2019
-
-    Examples
-    --------
-    Minimal example of usage. This would not produce a valid LAS 2.0 file since it is missing many of the mandatory
-    sections and lines.
-    >>> import las2
-    >>> from io import StringIO
-    >>> data = {}
-    >>> data['well'] = [{'mnemonic': 'NULL', 'unit': '', 'value': '-999.0', 'description': ''}]
-    >>> data['curve'] = [
-    ...     {'mnemonic': 'DEPT', 'unit': 'M', 'value': '', 'description': ''},
-    ...     {'mnemonic': 'GR', 'unit': 'API', 'value': '', 'description': ''}
-    ... ]
-    >>> data['data'] = np.array([
-    ...     [1000.0, 1000.2, 1000.4, 1100.0],
-    ...     [25.0, 26.0, np.nan, 75.0]
-    ... ])
-    >>> lasfile = StringIO()
-    >>> las2.write(lasfile, data)
-    >>> print(lasfile.getvalue())
-    ~WELL
-    NULL. -999.0 :
-    ~CURVE
-    DEPT.M    :
-    GR  .API  :
-    ~A
-    1000.0000 25.0000
-    1000.2000 26.0000
-    1000.4000 -999.0000
-    1100.0000 75.0000
-    """
-    if isinstance(lasfile, io.IOBase):
-        lasfile.seek(0)
-        close_file = False
-    else:
-        lasfile = open(lasfile, "w")
-        close_file = True
-
-    if section_titles is None:
-        section_titles = {}
-    for key, section in data.items():
-        if key not in section_titles:
-            section_titles[key] = _default_section_title_getters[key](key, section)
-
-    if section_formats is None:
-        section_formats = {}
-    for key, section in data.items():
-        if key not in section_formats:
-            section_formats[key] = _default_section_format_getters[key](section)
-
-    lines = []
-    for key in _sections_order:
-        if key not in data:
-            continue
-        composer = _composers[key]
-        format = section_formats[key]
-        lines.append(section_titles[key])
-        lines.extend(composer(data[key], format, data))
-    lasfile.write("\n".join(lines))
-
-    if close_file:
-        lasfile.close()
diff --git a/examples/porosity.py b/examples/porosity.py
deleted file mode 100644
index f70b213..0000000
--- a/examples/porosity.py
+++ /dev/null
@@ -1,287 +0,0 @@
-import numpy as np
-import numpy.typing as npt
-import warnings
-
-def density_porosity(rhob: npt.ArrayLike, rhom: float, rhof: float) -> np.ndarray:
-    """Estimate the porosity from the bulk density log [1]_.
-
-    Parameters
-    ----------
-    rhob : array_like
-        Bulk density log.
-    rhom : int, float
-        Matrix density.
-    rhof : int, float
-        Density of the fluid saturating the rock (Usually 1.0 for water and 1.1 for saltwater mud).
-       
-    Returns
-    -------
-    phi : array_like
-        Total porosity for the aimed interval using the bulk density.
-
-    References
-    ----------      
-    .. [1] Schön, J. H. (2015). Physical properties of rocks: Fundamentals and 
-    principles of petrophysics. Elsevier.
-
-    """
-    if rhom == rhof:
-        warnings.warn(UserWarning("This will result in a division by zero"))
-
-        return np.nan
-
-    else:
-        if any(rhom < rhof or rhom <= rhob):
-            warnings.warn(UserWarning("rhom must be greater than rhof and rhob"))
-
-            return (rhom - rhob) / (rhom - rhof)
-        
-        elif any(rhom - rhob > rhom - rhof):
-            warnings.warn(UserWarning("phi must be a value between 0 and 1"))
-
-            return (rhom - rhob) / (rhom - rhof)
-        
-        else: 
-            phi = (rhom - rhob) / (rhom - rhof)
-
-            return phi
-    
-
-def neutron_porosity(nphi: npt.ArrayLike, vsh: npt.ArrayLike,
-             nphi_sh: float) -> np.ndarray:
-    """Estimate the effective porosity from the neutron log [1]_.
-
-    Parameters
-    ----------
-    nphi : array_like
-        neutron log.
-    vsh : array_like
-        Total volume of shale in the rock, chosen the most representative.
-    phi_nsh : int, float
-        Apparent porosity read in the shales on and under the layer under study and with the same values used in φN.
-
-    Returns
-    -------
-    phin : array_like
-        Effective porosity from the neutron log for the aimed interval.
-
-    References
-    ----------
-    .. [1] Schön, J. H. (2015). Physical properties of rocks: Fundamentals and 
-    principles of petrophysics. Elsevier.
-
-    """
-    if any(nphi < (vsh * nphi_sh)):
-        warnings.warn(UserWarning("phin must be a positive value"))
-
-        return nphi - (vsh * nphi_sh)
-    
-    elif any(nphi - (vsh * nphi_sh) > 1):
-        warnings.warn(UserWarning("phin must be a value between 0 and 1"))
-
-        return nphi - (vsh * nphi_sh)
-
-    else:
-        phin = nphi - (vsh * nphi_sh)
-
-        return phin
-
-
-def neutron_density_porosity(phid: npt.ArrayLike, phin: npt.ArrayLike,
-                squared: bool = False) -> np.ndarray:
-    """Estimate the effective porosity by calculating the mean of Bulk Density porosity and Neutron porosity [1]_.
-
-    Parameters
-    ----------
-    phid : array_like
-        Effective porosity and shale free for the aimed interval using the bulk density.
-    phin : array_like
-        Effective porosity from the neutron log for the aimed interval.
-
-    Returns
-    -------
-    phie : array_like
-        Effective porosity from the Bulk Density porosity and Neutron porosity mean.
-
-    References
-    ----------
-    TODO
-
-    """
-    if squared == False:
-        if any((phid + phin / 2) > 1):
-            warnings.warn(UserWarning("phi must be a value between 0 and 1"))
-
-            return (phid + phin) / 2
-        else:
-            phi = (phid + phin) / 2
-
-            return phi
-
-    elif squared == True:
-        if any((phid**2 + phin**2 / 2) > 1):
-            warnings.warn(UserWarning("phi must be a value between 0 and 1"))
-
-            return np.sqrt( (phid**2 + phin**2) / 2)
-
-        else:
-            phi = np.sqrt( (phid**2 + phin**2) / 2)
-
-            return phi  
-
-
-#TODO phit -> phie (clay volume correction)
-
-
-def sonic_porosity(dt, dtma, dtf):
-
-    """Estimate the Porosity from sonic using the Wyllie time-average equation [1]_.
-
-    Parameters
-    ----------
-    dt : array_like
-        Sonic log reading (acoustic transit time (μsec/ft))
-    dtma : int, float
-        Acoustic transit time of the matrix (μsec/ft)
-    dtf : int, float
-        Acoustic transit time of the fluids, usually water (μsec/ft)
-              
-    Returns
-    -------
-    phidt : array_like
-        Porosity from sonic.
-
-    References
-    ----------
-    .. [1] M. R. J. Wyllie, A. R. Gregory, and L. W. Gardner, (1956), "ELASTIC WAVE VELOCITIES IN HETEROGENEOUS AND POROUS MEDIA," GEOPHYSICS 21: 41-70.
-
-    """
-    if dtf == dtma:
-        warnings.warn(UserWarning("This will result in a division by zero"))
-
-        return np.nan
-
-    else:
-        if any(dt <= dtma) or any(dtf <= dtma):
-            warnings.warn(UserWarning("dt and dtf must be greater than dtma"))
-
-            return (dt - dtma) / (dtf - dtma)
-
-        elif any(dt - dtma > dtf - dtma):
-            warnings.warn(UserWarning("phidt must be between 0 and 1"))
-
-            return (dt - dtma) / (dtf - dtma)
-
-        else:
-            phidt = (dt - dtma) / (dtf - dtma)
-
-            return phidt
-
-
-def gaymard_porosity(phid, phin):
-    """Estimate the effective porosity using Gaymard-Poupon [1]_ method.
-
-    Parameters
-    ----------
-    phid : array_like
-        Density porosity (porosity calculated using density log)
-    phin : int, float
-        Neutron porosity (porosity calculated using neutron log)
-
-    Returns
-    -------
-    phie : array_like
-        Effective porosity using Gaymard-Poupon method
-    
-    References
-    ----------
-    .. [1] Gaymard, R., and A. Poupon. "Response Of Neutron And Formation
-    Density Logs In Hydrocarbon Bearing Formations." The Log Analyst 9 (1968).
-
-    """
-    phie = (0.5 * (phid*phid + phin*phin)) ** 0.5
-
-    return phie
-
-
-_porosity_methods = {
-    "density": density_porosity,
-    "neutron": neutron_porosity,
-    "neutron-density": neutron_density_porosity,
-    "sonic": sonic_porosity,
-    "gaymard": gaymard_porosity
-}
-
-
-def porosity(method: str = "density", **kwargs):
-    """Compute porosity from well logs.
-
-    This is a façade for the methods:
-        - density
-        - neutron
-        - neutron-density
-        - sonic
-        - gaymard
-
-    Parameters
-    ----------
-    rhob : array_like
-        Bulk density log. Required if `method` is "denisty".
-    rhom : int, float
-        Matrix density. Required if `method` is "denisty".
-    rhof : int, float
-        Density of the fluid saturating the rock (Usually 1.0 for water and 1.1 for saltwater mud). Required if `method` is "denisty".
-    nphi : array_like
-        Neutron log. Required if `method` is "neutron".
-    vsh : array_like
-        Total volume of shale in the rock, chosen the most representative. Required if `method` is "neutron".
-    phi_nsh : int, float
-        Apparent porosity read in the shales on and under the layer under study and with the same values used in φN. Required if `method` is "neutron".
-    dt : array_like
-        Sonic log reading (acoustic transit time (μsec/ft)). Required if `method` is "sonic".
-    dtma : int, float
-        Acoustic transit time of the matrix (μsec/ft). Required if `method` is "sonic".
-    dtf : int, float
-        Acoustic transit time of the fluids, usually water (μsec/ft). Required if `method` is "sonic".
-    phid : array_like
-        Density porosity (porosity calculated using density log). Required if `method` is "neutron-density" or "gaymard.
-    phin : int, float
-        Neutron porosity (porosity calculated using neutron log). Required if `method` is "neutron-density" or "gaymard.
-    method : str, optional
-        Name of the method to be used.  Should be one of
-            - 'density'
-            - 'neutron'
-            - 'neutron-density'
-            - 'sonic'
-            - 'gaymard'
-        If not given, default method is 'density'
-
-    Returns
-    -------
-    phi : array_like
-        Porosity log using the defined method.
-
-    """
-    options = {}
-
-    required = []
-    if method == "density":
-        required = ["rhob", "rhom", "rhof"]
-    elif method == "neutron":
-        required = ["nphi", "vsh", "nphi_sh"]
-    elif method == "neutron-density":
-        required = ["phid", "phin"]
-    elif method == "sonic":
-        required = ["dt", "dtma", "dtf"]
-    elif method == "gaymard":
-        required = ["phid", "phin"]
-
-    for arg in required:
-        if arg not in kwargs:
-            msg = f"Missing required argument for method '{method}': '{arg}'"
-            raise TypeError(msg)
-        options[arg] = kwargs[arg]
-
-    fun = _porosity_methods[method]
-
-    return fun(**options)
diff --git a/examples/shale_volume.py b/examples/shale_volume.py
deleted file mode 100644
index 46a2d5e..0000000
--- a/examples/shale_volume.py
+++ /dev/null
@@ -1,247 +0,0 @@
-import numpy as np
-import numpy.typing as npt
-
-
-def gammarayindex(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
-    """Calculates the gamma ray index.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value. 
-
-    Returns
-    -------
-    igr : array_like
-        The gamma ray index varying between 0.0 (clean sand) and 1.0 (shale).
-    
-    """
-    if grmin == grmax:
-        msg = "Division by zero. The value of grmin is equal to the value of grmax."
-        raise ZeroDivisionError(msg)
-
-    igr = (gr - grmin) / (grmax - grmin)
-    igr = np.clip(igr, 0.0, 1.0)
-
-    return igr
-
-
-def vshale_linear(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
-    """Estimate the shale volume from the linear model.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value. 
-
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the Linear method.
-
-    """ 
-    vshale = gammarayindex(gr, grmin, grmax)
-
-    return vshale
-
-
-def vshale_larionov_old(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
-    """Estimate the shale volume from the Larionov model for old rocks.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value.  
-
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the Larionov method.
-
-    """
-    igr = gammarayindex(gr, grmin, grmax)
-    vshale = 0.33 * (2. ** (2. * igr) - 1)
-
-    return vshale
-
-
-def vshale_larionov(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
-    """Estimate the shale volume from the Larionov model for young rocks.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value.
-         
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the Larionov method.
-
-    """
-    igr = gammarayindex(gr, grmin, grmax)
-    vshale = 0.083 * (2 ** (3.7 * igr) - 1)
-
-    return vshale
-
-
-def vshale_clavier(gr: npt.ArrayLike, grmin: float, grmax: float):
-    """Estimate the shale volume from the Clavier model.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value.
-         
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the Clavier method.
-    
-    """
-    igr = gammarayindex(gr, grmin, grmax)
-    vshale = 1.7 - np.sqrt(3.38 - (igr + 0.7) ** 2)
-
-    return vshale
-
-
-def vshale_stieber(gr: npt.ArrayLike, grmin: float, grmax: float):
-    """Estimate the shale volume from the Stieber model.
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value.
-         
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the Stieber method.
-
-    """
-    igr = gammarayindex(gr, grmin, grmax)
-    vshale = igr / (3 - 2 * igr)
-
-    return vshale
-
-
-def vshale_neu_den(neu: npt.ArrayLike, den: npt.ArrayLike, cl1_n: float,
-                   cl1_d: float, cl2_n: float, cl2_d: float, clay_n: float,
-                   clay_d: float) -> np.ndarray:
-    """Estimates the shale volume from neutron and density logs method [1]_.
-
-    Parameters
-    ----------
-    neu : array_like
-        Neutron porosity log.
-    den : array_like
-        Bulk density log.
-    cl1_n : int, float
-        Neutron porosity value from clean point 1.
-    cl1_d : int, float
-        Bulk density value from clean point 1.
-    cl2_n : int, float
-        Neutron porosity value from clean point 2.
-    cl2_d : int, float
-        Bulk density value from clean point 2.
-    clay_n : int, float
-        Neutron porosity value from clay point.
-    clay_d : int, float
-        Bulk density value from clay point.
-
-    Returns
-    -------
-    vshale : array_like
-        Shale volume from neutron and density logs method.
-
-    References
-    ----------
-    .. [1] Bhuyan, K., & Passey, Q. R. (1994). Clay estimation from GR and 
-    neutron-density porosity logs. In SPWLA 35th Annual Logging Symposium. 
-    OnePetro.
-
-    """
-    x1 = (cl2_d - cl1_d) * (neu - cl1_n)
-    x2 = (den - cl1_d) * (cl2_n - cl1_n)
-    x3 = (cl2_d - cl1_d) * (clay_n - cl1_n)
-    x4 = (clay_d - cl1_d) * (cl2_n - cl1_n)
-    vshale = (x1-x2) / (x3-x4)
-
-    return vshale
-
-
-_vshale_methods = {
-    "linear": vshale_linear,
-    "larionov": vshale_larionov,
-    "larionov_old": vshale_larionov_old,
-    "clavier": vshale_clavier,
-    "stieber": vshale_stieber,
-}
-
-
-def vshale(gr: npt.ArrayLike, grmin: float, grmax: float, method: str = None) -> np.ndarray:
-    """Compute the shale volume from gamma ray log.
-
-    This is a façade for the methods:
-        - vshale_linear
-        - vshale_larionov
-        - vshale_larionov_old
-        - vshale_clavier
-        - vshale_stieber
-
-    Parameters
-    ----------
-    gr : array_like
-        Gamma Ray log.
-    grmin : int, float
-        Clean sand GR value.
-    grmax : int, float
-        Shale/clay value.
-    method : str, optional
-        Name of the method to be used.  Should be one of
-            - 'linear'
-            - 'larionov'
-            - 'larionov_old'
-            - 'clavier'
-            - 'stieber'
-        If not given, default method is 'linear'
-
-    Returns
-    -------
-    vshale : array_like
-        Shale Volume for the aimed interval using the defined method.
-    """
-    if method is None:
-        method = "linear"
-
-    if method not in _vshale_methods:
-        msg = f"Method not found: {method}"
-        raise ValueError(msg)
-    
-    fun = _vshale_methods[method]
-
-    return fun(gr, grmin, grmax)
diff --git a/stoneforge/tests_rock_physics/__init__.py b/pip
similarity index 100%
rename from stoneforge/tests_rock_physics/__init__.py
rename to pip
diff --git a/setup.py b/setup.py
index 9d3e320..413b0fd 100644
--- a/setup.py
+++ b/setup.py
@@ -25,7 +25,17 @@
         "pytest>=6.2.2, <6.2.5",
         "scipy>=1.4.1, <1.8.1",
         "scikit-learn>=0.22.1, <0.24.2",
-        "xgboost==1.4.0",
-        "lightgbm==3.3.2"
+        #"xgboost==1.4.0",
+        "matplotlib>=3.5.0, <3.5.3",
+        "pandas==1.5.2",
+        "catboost==1.0.6",
+        "lightgbm==3.3.2",
+        #"catboost==0.26.1"
+        #"auto-sklearn==0.12.5"
+        
+        #"matplotlib", ### TO REMOVE BEFORE MERGE!!
+        #"pandas", ### TO REMOVE BEFORE MERGE!!
+        #"jupyter", ### TO REMOVE BEFORE MERGE!!
+        #"seaborn" ### # TO REMOVE BEFORE MERGE!!
     ],
-)
+)
\ No newline at end of file
diff --git a/stoneforge/__init__.py b/stoneforge/__init__.py
index 682c1bf..46fc958 100644
--- a/stoneforge/__init__.py
+++ b/stoneforge/__init__.py
@@ -1,6 +1,9 @@
 from . import petrophysics  # noqa: F401
-from . import rock_physics  # noqa: F401
 from . import pseudo_wells  # noqa: F401
-from . import tvdss  # noqa: F401
+
 from . import machine_learning  # noqa: F401
-from . import preprocessing  # noqa: F401
\ No newline at end of file
+from . import preprocessing  # noqa: F401
+from . import rock_physics  # noqa: F401
+
+from . import inversion  # noqa: F401
+from . import wavelets  # noqa: F401
\ No newline at end of file
diff --git a/stoneforge/data_replacement/__init__.py b/stoneforge/data_replacement/__init__.py
new file mode 100644
index 0000000..f53af65
--- /dev/null
+++ b/stoneforge/data_replacement/__init__.py
@@ -0,0 +1,3 @@
+from .fit import fit
+from .predict import predict
+from .settings import settings
\ No newline at end of file
diff --git a/stoneforge/data_replacement/evaluation.py b/stoneforge/data_replacement/evaluation.py
new file mode 100644
index 0000000..da68533
--- /dev/null
+++ b/stoneforge/data_replacement/evaluation.py
@@ -0,0 +1,37 @@
+import numpy as np
+from sklearn.metrics import mean_absolute_percentage_error
+from sklearn.metrics import mean_squared_error
+#import pickle
+import json
+
+
+def _saves(file, name):
+    with open(name+'.json', 'w') as write_file:
+        json.dump(file, write_file)
+
+
+def evaluation(y_m, y, decimals = 3, path = '.'):
+
+    json_dict = {}
+
+    json_dict['mean_absolute_percentage_error'] = np.round(mean_absolute_percentage_error(y_m,y),decimals)
+
+    #print(list(confusion_matrix(y_m,y)),'\n')
+    #print(list(precision_recall_fscore_support(y_m,y)))
+    #json_dict['confusion_matrix'] = list(confusion_matrix(y_m,y))
+    #json_dict['precision_recall_fscore'] = list(precision_recall_fscore_support(y_m,y))
+
+    lito = list(set(y))
+    json_dict['facies'] = lito
+
+    prf = []
+    for i in list(mean_squared_error(y_m,y, labels = np.array(lito))):
+        values = np.round(i,decimals)
+        values = np.array(values,dtype='str')
+        prf.append(list(values))
+    json_dict['mean_squared_error'] = prf
+    
+    if path:
+        _saves(json_dict, path+'\\evaluation_metrics')
+    if not path:
+        return json_dict
\ No newline at end of file
diff --git a/stoneforge/data_replacement/fit.py b/stoneforge/data_replacement/fit.py
new file mode 100644
index 0000000..89c1602
--- /dev/null
+++ b/stoneforge/data_replacement/fit.py
@@ -0,0 +1,264 @@
+import numpy as np
+import numpy.typing as npt
+import pickle
+import json
+import warnings
+
+
+from sklearn.tree import DecisionTreeRegressor
+from sklearn.svm import SVC
+from sklearn.linear_model import LogisticRegression
+from sklearn.ensemble import RandomForestRegressor
+import lightgbm as LGBMRegressor
+from catboost.core import CatBoostRegressor
+from sklearn.model_selection import GridSearchCV
+from sklearn.preprocessing import PolynomialFeatures
+from sklearn.linear_model import LinearRegression
+from xgboost import XGBRegressor
+from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
+from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import StandardScaler
+from sklearn.preprocessing import LabelEncoder
+from sklearn.preprocessing import MinMaxScaler
+
+
+
+def saves(file, name):
+    with open(name + ".pkl", "wb") as write_file:
+        pickle.dump(file, write_file)
+
+
+#Simple Linear Regression
+def linear_regression_replacement(X: npt.ArrayLike, y: npt.ArrayLike, path, **kwargs):
+
+    f1 = open(path + '\\linear_regression_settings.json')
+    f2 = open(path + '\\polinomial_settings.json')
+
+    settings = json.load(f1)
+    pol_settings = json.load(f2)
+
+    pol_degree = PolynomialFeatures(degree=pol_settings['degree'])
+    X_poly = pol_degree.fit_transform(X)
+
+    slregression = LinearRegression(**settings)
+    slregression.fit(X_poly, y, **kwargs)
+
+    saves(slregression, path+"\\linear_regression_fit_property")
+    
+
+#Suporte Vector 
+def suporte_vector_replacement(X: npt.ArrayLike, y: npt.ArrayLike, path, **kwargs):
+
+    f = open(path + '\\support_vector_settings.json')
+
+    settings = json.load(f)
+    if not settings:
+        settings['random_state'] = 99
+
+    svn = SVC(**settings)
+
+    svn.fit(X, y, **kwargs)
+    
+    saves(svn, path+"\\suporte_vector_fit_property")
+
+
+
+#Decison Tree
+def decision_tree_replacement(X: npt.ArrayLike, y: npt.ArrayLike, path,gs=True, **kwargs):
+
+    if gs:
+        parameters = {'criterion': ['gini', 'entropy'],
+        'max_depth':[5,10,15,30,50,70,100],
+        'random_state':[99]}
+
+        decisiontree = DecisionTreeRegressor()
+
+        bestdt = GridSearchCV(decisiontree,parameters,scoring='accuracy')
+        bestdt.fit(X,y)
+        settings = bestdt.best_params_
+
+    if not gs:
+        f = open(path + '\\decision_tree_replacement.json')
+        settings = json.load(f)
+        if not settings:
+            settings['random_state'] = 99
+    
+    d_treer = DecisionTreeRegressor(**settings)
+    d_treer.fit(X, y, **kwargs)
+    
+    saves(d_treer, path+"\\decision_tree_fit_property")
+
+
+#Random Florest
+def random_florest_replecement(X: npt.ArrayLike, y: npt.ArrayLike, path, gs=True,**kwargs):
+
+    if gs:
+        parameters = {'criterion': ['gini', 'entropy'],
+        'max_depth':[5,10,15,30,50,70,100],
+        'random_state':[99]}
+
+        randomflorest = RandomForestRegressor()
+
+        bestrf = GridSearchCV(randomflorest,parameters,scoring='accuracy')
+        bestrf.fit(X,y)
+        settings = bestrf.best_params_
+
+    if not gs:
+        f = open(path + '\\random_florest_settings.json')
+        setting = json.load(f)
+        if not settings:
+            settings['random_state'] = 99
+    
+    d_florestc = RandomForestRegressor(**settings)
+    d_florestc.fit(X, y, **kwargs)
+    
+    saves(d_florestc, path+"\\random_florest_fit_property")
+
+
+#XgBoost
+def xgboost_replacement(X: npt.ArrayLike, y: npt.ArrayLike, path,gs=False, **kwargs) -> np.ndarray:
+
+    if gs:
+        parameters =  {'n_estimators': [100],
+        'learning_rate': [0.5],
+        'max_depth':[5,10,15,30,50,70,100]}
+
+        xgb = XGBRegressor()
+
+        bestxgbc = GridSearchCV(xgb,parameters,scoring='accuracy')
+        bestxgbc.fit(X,y)
+        #bestxgb = bestxgb.best_params_
+        settings = bestxgbc.best_params_
+
+    if not gs:
+        f = open(path + '\\xgboost_regression_settings.json')
+        settings = json.load(f)
+    
+    xg = XGBRegressor(**settings)
+    xg.fit(X, y, **kwargs)
+
+    saves(xg, path+"\\xgboost_fit_property")
+
+#LightGBM
+def lightgbm_replacement(X: npt.ArrayLike, y: npt.ArrayLike, path, gs=False, **kwargs):
+
+    if gs:
+        parameters =  {'n_estimators': [100],
+        'learning_rate': [0.5],
+        'max_depth':[5,10,15,30,50,70,100],
+        'random_state':[99]}
+
+        lghtr = LGBMRegressor()
+
+        bestlight = GridSearchCV(lghtr,parameters,scoring='accuracy')
+        bestlight.fit(X,y)
+        #bestxgb = bestxgb.best_params_
+        settings = bestlight.best_params_
+
+    if not gs:
+        f = open(path + '\\lightgbm_florest_settings.json')
+        settings = json.load(f)
+        if not settings:
+            settings['random_state'] = 99
+    
+    xg = LGBMRegressor(**settings)
+    xg.fit(X, y, **kwargs)
+
+    saves(xg, path+"\\lightgbm_replacement_fit_property")
+
+#CatBoost
+def catboost_replecement(X: npt.ArrayLike, y: npt.ArrayLike, path,gs=False, **kwargs) -> np.ndarray:
+
+    if gs:
+        parameters =  {'n_estimators': [100,150,200],
+        'learning_rate': [0.3,0.5,0.7],
+        'max_depth':[5,10,15,30,50,70,100],
+        'random_state':[99]}
+
+        cat = CatBoostRegressor()
+
+        bestcatr = GridSearchCV(cat,parameters,scoring='accuracy')
+        bestcatr.fit(X,y)
+        #bestcat = bestcat.best_params_
+        settings = bestcatr.best_params_
+
+    if not gs:
+        f = open(path + '\\catboost_settings.json')
+        settings = json.load(f)
+        if not settings:
+            settings['random_state'] = 99
+    
+    cb = CatBoostRegressor(**settings)
+    cb.fit(X, y, **kwargs)
+
+    saves(cb, path+"\\catboost_fit_property")
+
+
+
+_fit_methods = {
+    "linear_regression_simple": linear_regression_replacement,
+    "linear_regression_polynomial": linear_regression_replacement,
+    "suporte_vector_regression": suporte_vector_replacement,
+    "decision_tree_regression": decision_tree_replacement,
+    "random_florest_regression": random_florest_replecement,
+    "xgboost_regression": xgboost_replacement,
+    "lightgbm_regression": lightgbm_replacement,
+    "catboost_regression": catboost_replecement
+    }
+
+
+def fit(X: npt.ArrayLike , y: npt.ArrayLike, method: str = "linear_regression_simple", path = ".", **kwargs):
+
+    print(method)
+    if method == "linear_regression_simple":
+        fun = _fit_methods[method]
+    if method == "linear_regression_polynomial":
+        fun = _fit_methods[method]
+    if method == "suporte_vector_regression":
+        fun = _fit_methods[method]
+    if method == "decision_tree_regression":
+        fun = _fit_methods[method]
+    if method == "random_florest_regression":
+        fun = _fit_methods[method]
+    if method == "xgboost_regression":
+        fun = _fit_methods[method]
+    if method == "lightgbm_regression":
+        fun = _fit_methods[method]
+    if method == "catboost_regression":
+        fun = _fit_methods[method]
+
+    # ===================================== #
+
+    scaler = MinMaxScaler()
+    scaler.fit(X)
+    X_norm = scaler.transform(X)
+    saves(scaler, path+"\\scaler")
+    
+    #Normalization adjusts the values of a variable to a specific range.
+
+    # ===================================== #
+
+    scalerp = StandardScaler()
+    scalerp.fit(X_norm)
+    X_norm = scaler.transform(X_norm)
+    saves(scalerp, path+"\\scalerp")
+
+    # ===================================== #
+    
+    #Standardization transforms the data in such a way that it has a mean of zero and a standard deviation of one.
+
+    # TODO: repass to preprocessing due to the sobreposition of processes
+
+    #scaler = MinMaxScaler()
+    #scaler.fit(y)
+    #y_norm = scaler.transform(y)
+    #saves(scaler, path+"\\y_scaler")
+        
+    #scalerp = StandardScaler()
+    #scalerp.fit(y_norm)
+    #y_norm = scaler.transform(y_norm)
+    #saves(scalerp, path+"\\y_scalerp")
+    
+
+    fun(X_norm, y, path, **kwargs)
+    #fun(X, y, path, **kwargs)
diff --git a/stoneforge/data_replacement/predict.py b/stoneforge/data_replacement/predict.py
new file mode 100644
index 0000000..1a52415
--- /dev/null
+++ b/stoneforge/data_replacement/predict.py
@@ -0,0 +1,116 @@
+import numpy as np
+import numpy.typing as npt
+import pickle
+import warnings
+import json
+
+from sklearn.linear_model import LinearRegression
+from sklearn.linear_model import LogisticRegression
+from sklearn.svm import SVR
+from sklearn.tree import DecisionTreeRegressor
+from sklearn.ensemble import RandomForestRegressor
+from sklearn.preprocessing import PolynomialFeatures
+from xgboost import XGBRegressor
+import lightgbm as lgb
+from catboost.core import CatBoostRegressor
+
+
+def linear_regression_replacement(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
+
+    slregression = pickle.load(open(path+"\\linear_regression_fit_property.pkl", 'rb'))
+    f = open(path + '\\polinomial_settings.json')
+    pol_settings = json.load(f)
+
+    pol_degree = PolynomialFeatures(degree=pol_settings['degree'])
+    x_poly = pol_degree.fit_transform(x)
+
+    return slregression.predict(x_poly , **kwargs)
+
+
+def support_vector_replacement(x: npt.ArrayLike, path, **kwargs) -> np.ndarray:
+
+    svnegression = pickle.load(open(path+"\\support_vector_fit_property.pkl", 'rb'))
+
+    return svnegression.predict(x, **kwargs)
+
+
+def decision_tree_replacement(x: npt.ArrayLike, path, **kwargs) -> np.ndarray:
+
+    d_treec_regression = pickle.load(open(path+"\\decision_tree_fit_property.pkl", 'rb'))
+
+    return d_treec_regression.predict(x, **kwargs)
+
+
+def random_florest_replecement(x: npt.ArrayLike, path, **kwargs) -> np.ndarray:
+
+    randomregression = pickle.load(open(path+"\\random_florest_fit_property.pkl", 'rb'))
+    
+    return randomregression.predict(x, **kwargs)
+
+
+def xgboost_replacement(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
+
+    xgboostregression = pickle.load(open(path+"\\xgboost_fit_property.pkl", 'rb'))
+
+    return xgboostregression.predict(x,**kwargs)
+
+
+def lightgbm_replacement(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
+
+    lightregression = pickle.load(open(path+"\\lightgbm_fit_property.pkl", 'rb'))
+    
+    return lightregression.predict(x,**kwargs)
+
+def catboost_replecement(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
+
+    catregression = pickle.load(open(path+"\\catboost_fit_property.pkl", 'rb'))
+    
+    return catregression.predict(x,**kwargs)
+
+
+
+_predict_methods = {
+    "linear_regression_simple": linear_regression_replacement,
+    "linear_regression_polynomial": linear_regression_replacement,
+    "suporte_vector_regression": support_vector_replacement,
+    "decision_tree_regression": decision_tree_replacement,
+    "random_florest_regression": random_florest_replecement,
+    "xgboost_regression": xgboost_replacement,
+    "lightgbm_regression": lightgbm_replacement,
+    "catboost_regression": lightgbm_replacement,
+    }
+
+
+def predict(x: npt.ArrayLike, method: str = "linear_regression_simple", path = ".", **kwargs):
+
+    if method == "linear_regression_simple":
+        fun = _predict_methods[method]
+    if method == "linear_regression_polynomial":
+        fun = _predict_methods[method]
+    if method == "suporte_vector_regression":
+        fun = _predict_methods[method]
+    if method == "decision_tree_regression":
+        fun = _predict_methods[method]
+    if method == "random_florest_regression":
+        fun = _predict_methods[method]
+    if method == "xgboost_regression":
+        fun = _predict_methods[method]
+    if method == "lightgbm_regression":
+        fun= _predict_methods[method]
+    if method == "catboost_regression":
+        fun= _predict_methods[method]
+
+    scaler = pickle.load(open(path+"\\scaler.pkl", 'rb'))
+    scalerp = pickle.load(open(path+"\\scalerp.pkl", 'rb'))
+    #y_scalerp = pickle.load(open(path+"\\y_scalerp.pkl", 'rb'))
+    #scaler.fit(x)
+
+    x_norm = scaler.transform(x)
+    x_norm = scalerp.transform(x_norm)
+
+    y = fun(x_norm, path, **kwargs)
+
+    #y_norm = scaler.transform(y)
+    #y_norm = scalerp.transform(y_norm)
+
+    return y
diff --git a/stoneforge/data_replacement/settings.py b/stoneforge/data_replacement/settings.py
new file mode 100644
index 0000000..9c0983e
--- /dev/null
+++ b/stoneforge/data_replacement/settings.py
@@ -0,0 +1,60 @@
+import numpy as np
+import numpy.typing as npt
+import json
+import warnings
+
+# TODO: if method is not listed do not execute and gives error to the user
+
+LR_METHODS = [
+    "decision_tree_regression",
+    "suporte_vector_regression",
+    "linear_regression",
+    "random_forest_regression",
+    'lightgbm_regression',
+    'xgboost_regression'
+    'catboost_regression'
+]
+
+def saves(file, name):
+    with open(name+'.json', 'w') as write_file:
+        json.dump(file, write_file)
+
+def settings(method: str = "linear_regression", path = ".", **kwargs):
+
+    if method == "linear_regression" or method == "linear_regression_simple" or method  =="linear_regression_polynomial":
+        new_settings = {}
+        if not 'degree' in kwargs:
+            saves({'degree':1}, path+"\\polinomial_settings")
+            new_settings = kwargs
+        else:
+            saves({'degree':kwargs['degree']}, path+"\\polinomial_settings")
+            new_settings = {}
+            for k in kwargs:
+                if k != 'degree':
+                    new_settings[k] = kwargs[k]
+    
+        saves(new_settings, path+"\\linear_regression_settings")
+        
+
+    if method == "suporte_vector_regression":
+        saves(kwargs, path+"\\support_vector_settings")
+
+    if method == "decision_tree_regression":
+        saves(kwargs, path+"\\decision_tree_settings")
+
+    if method == "random_forest_regression":
+        saves(kwargs, path+"\\random_forest_settings")
+
+    if method == "xgboost_regression":
+        saves(kwargs, path+"\\xgboost_regression_settings")
+
+    if method == "lightgbm_regression":
+        saves(kwargs, path+"\\lightgbm_settings")
+
+    if method == "catboost_regression":
+        saves(kwargs, path+"\\catboost_settings")
+
+    saves(LR_METHODS, path+'\\all_methods')
+
+
+
diff --git a/stoneforge/inversion/__init__.py b/stoneforge/inversion/__init__.py
new file mode 100644
index 0000000..5a09507
--- /dev/null
+++ b/stoneforge/inversion/__init__.py
@@ -0,0 +1,1 @@
+from . import regularized_acoustic_reflectivy_inversion  # noqa: F401
\ No newline at end of file
diff --git a/stoneforge/inversion/regularized_acoustic_reflectivy_inversion.py b/stoneforge/inversion/regularized_acoustic_reflectivy_inversion.py
new file mode 100644
index 0000000..0166edb
--- /dev/null
+++ b/stoneforge/inversion/regularized_acoustic_reflectivy_inversion.py
@@ -0,0 +1,40 @@
+#Programa que implementa computacionalmente Inversao de traco sismico por deconvolucao sparse spike usando o algoritmo de variacao total e minimos quadrados
+
+import numpy as np 
+import matplotlib.pyplot as plt
+from scipy.linalg import toeplitz
+
+def IRLS_Inv(trace, G, alphaL1, alphaL2,thresold,niter):
+    residuo_iter = np.zeros(10)
+    dim = len(trace)
+    R = np.eye(dim)
+    I = np.eye(dim)
+    G_T = G.transpose()
+    count = 0 
+    #Tikhonov ordem zero:
+    M1_L2 = np.linalg.inv( np.matmul(G_T, G) + (alphaL2*I) )
+    M2_L2 = np.matmul(G_T, trace)
+    RegL2 = np.matmul(M1_L2, M2_L2)
+
+    #Inversao do traco sismico utilizando regularizacao de tikhonov a partir da norma1 nos residuos dos dados
+    while (count < niter):
+            Gt_R = np.matmul(G_T, R)
+            M1_L1 = np.linalg.inv( np.matmul(Gt_R,G) + (alphaL1*I) )
+            M2_L1 = np.matmul(Gt_R, trace)
+            RegL1 = np.matmul(M1_L1, M2_L1)
+            dcalc = np.matmul(G, RegL1)
+            residuo = dcalc[:] - trace[:]
+         
+            for i in range( (dim//2)+2 ):
+                if abs(residuo[i]) >= thresold:
+                    R[i,i] = 1/abs(residuo[i])
+                else:
+                    R[i,i] = 1/thresold
+            for i in range(dim):
+                if abs(RegL1[i]) >= thresold:
+                    I[i,i] = 1/abs(RegL1[i])
+                else:
+                    I[i,i] = 1/thresold
+            residuo_iter[count] = residuo[145]
+            count = count + 1
+    return RegL2, RegL1, residuo_iter
\ No newline at end of file
diff --git a/stoneforge/machine_learning/fit.py b/stoneforge/machine_learning/fit.py
index abbdab3..9efba49 100644
--- a/stoneforge/machine_learning/fit.py
+++ b/stoneforge/machine_learning/fit.py
@@ -10,7 +10,7 @@
 from sklearn.linear_model import LogisticRegression
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.ensemble import RandomForestClassifier
-from xgboost import XGBClassifier
+#from xgboost import XGBClassifier
 from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
@@ -147,6 +147,7 @@ def random_florest(X: npt.ArrayLike, y: npt.ArrayLike, path, gs =False, **kwargs
 
 
 #XGBOOST
+"""
 def xgboost(X: npt.ArrayLike, y: npt.ArrayLike, path, gs=False, **kwargs) -> np.ndarray:
 
     if gs:
@@ -171,6 +172,7 @@ def xgboost(X: npt.ArrayLike, y: npt.ArrayLike, path, gs=False, **kwargs) -> np.
     xg.fit(X, y, **kwargs)
 
     saves(xg, path+"\\xgboost_fit_property")
+"""
 
 
 #CatBoost
@@ -208,7 +210,7 @@ def catboost(X: npt.ArrayLike, y: npt.ArrayLike, path, gs=False, **kwargs) -> np
     "LogisticRegression": logistic_regression,
     "KNeighborsClassifier": k_nearest_neighbors,
     "RandomForestClassifier": random_florest,
-    'XGBClassifier': xgboost,
+    #'XGBClassifier': xgboost,
     #'CatBoostClassifier': catboost
     #'AutomlClassifier': automl 
     }
diff --git a/stoneforge/machine_learning/predict.py b/stoneforge/machine_learning/predict.py
index b282321..d02bb2c 100644
--- a/stoneforge/machine_learning/predict.py
+++ b/stoneforge/machine_learning/predict.py
@@ -9,7 +9,7 @@
 from sklearn.linear_model import LogisticRegression
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.ensemble import RandomForestClassifier
-from xgboost import XGBClassifier
+#from xgboost import XGBClassifier
 from sklearn.preprocessing import StandardScaler
 #from catboost import CatBoostClassifier
 from sklearn.preprocessing import LabelEncoder
@@ -54,11 +54,11 @@ def random_florest(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
     
     return d_florest.predict(x,**kwargs)
 
-def xgboost(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
+#def xgboost(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
 
-    xg = pickle.load(open(path+"\\xgboost_fit_property.pkl", 'rb'))
+#    xg = pickle.load(open(path+"\\xgboost_fit_property.pkl", 'rb'))
     
-    return xg.predict(x,**kwargs)
+#    return xg.predict(x,**kwargs)
 
 #def catboost(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
 
@@ -80,7 +80,7 @@ def xgboost(x: npt.ArrayLike, path, **kwargs)-> np.ndarray:
     "LogisticRegression": logistic_regression,
     "KNeighborsClassifier": k_nearest_neighbors,
     "RandomForestClassifier": random_florest,
-    'XGBClassifier': xgboost,
+    #'XGBClassifier': xgboost,
     #'CatBoostClassifier': catboost
     #'AutomlClassifier': automl 
     }
diff --git a/stoneforge/machine_learning/settings.py b/stoneforge/machine_learning/settings.py
index 8651981..e16a617 100644
--- a/stoneforge/machine_learning/settings.py
+++ b/stoneforge/machine_learning/settings.py
@@ -10,7 +10,7 @@
     "LogisticRegression",
     "KNeighborsClassifier",
     "RandomForestClassifier",
-    'XGBClassifier',
+    #'XGBClassifier',
     'CatBoostClassifier'
 ]
 
@@ -39,8 +39,8 @@ def settings(method: str = "GaussianNB", path = ".", **kwargs):
     if method == "RandomForestClassifier":
         saves(kwargs, path+'\\random_florest_settings')
 
-    if method == "XGBClassifier":
-        saves(kwargs, path+'\\xgboost_settings')
+    #if method == "XGBClassifier":
+    #    saves(kwargs, path+'\\xgboost_settings')
 
     if method == "CatBoostClassifier":
         saves(kwargs, path+'\\catboost_settings')
diff --git a/stoneforge/machine_learning/validation.py b/stoneforge/machine_learning/validation.py
index d611ff7..2663992 100644
--- a/stoneforge/machine_learning/validation.py
+++ b/stoneforge/machine_learning/validation.py
@@ -14,7 +14,7 @@
 from sklearn.linear_model import LogisticRegression
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.ensemble import RandomForestClassifier
-from xgboost import XGBClassifier
+#from xgboost import XGBClassifier
 from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
@@ -202,7 +202,7 @@ def  catboost(X: npt.ArrayLike, y: npt.ArrayLike, path, n_splits, random_state,
     "LogisticRegression": logistic_regression,
     "KNeighborsClassifier": k_nearest_neighbors,
     "RandomForestClassifier": random_florest,
-    'XGBClassifier': xgboost,
+    #'XGBClassifier': xgboost,
     #'CatBoostClassifier': catboost
     #'AutomlClassifier': automl 
     }
@@ -224,8 +224,8 @@ def validation(X: npt.ArrayLike , y: npt.ArrayLike, method: str = "GaussianNB",
         fun = _fit_methods[method]
     if method == "RandomForestClassifier":
         fun = _fit_methods[method]
-    if method == "XGBClassifier":
-        fun = _fit_methods[method]
+    #if method == "XGBClassifier":
+    #    fun = _fit_methods[method]
     #if method == "CatBoostClassifier":
     #    fun = _fit_methods[method]
     #if method == "AutoML":
diff --git a/stoneforge/petrophysics/helpers.py b/stoneforge/petrophysics/helpers.py
new file mode 100644
index 0000000..8311bce
--- /dev/null
+++ b/stoneforge/petrophysics/helpers.py
@@ -0,0 +1,7 @@
+
+# Ensure petrophysic output data (water saturation, shale volue and porosity) be at range [0, 1]
+def correct_petrophysic_estimation_range(petrophysics_data):
+    petrophysics_data[petrophysics_data > 1] = 1
+    petrophysics_data[petrophysics_data < 0] = 0
+
+    return petrophysics_data
\ No newline at end of file
diff --git a/stoneforge/petrophysics/porosity.py b/stoneforge/petrophysics/porosity.py
index a44e9e3..4bf6830 100644
--- a/stoneforge/petrophysics/porosity.py
+++ b/stoneforge/petrophysics/porosity.py
@@ -1,11 +1,36 @@
 import numpy as np
 import numpy.typing as npt
 import warnings
+from stoneforge.petrophysics.helpers import correct_petrophysic_estimation_range
 
-# Make anomalous water saturation values larger than 1 be one
-def correct_range(phi: np.ndarray):
-    phi[phi < 0] = 0
-    return phi
+
+
+
+def effective_porosity(phi: npt.ArrayLike, vsh: npt.ArrayLike) -> np.ndarray:
+    """Calculate the effective porosity from the total porisity and shale volume_.
+
+    Parameters
+    ----------
+    phi : array_like
+        Bulk density log.
+    vsh : int, float
+        Matrix density.
+       
+    Returns
+    -------
+    phie : array_like
+        Total porosity for the aimed interval using the bulk density.
+
+    References
+    ----------      
+    .. [1] Schön, J. H. (2015). Physical properties of rocks: Fundamentals and 
+    principles of petrophysics. Elsevier.
+
+    """
+    phie = phi - vsh
+
+    phie = correct_petrophysic_estimation_range(phie)
+    return phie
 
 def density_porosity(rhob: npt.ArrayLike, rhom: float, rhof: float) -> np.ndarray:
     """Estimate the porosity from the bulk density log [1]_.
@@ -49,7 +74,8 @@ def density_porosity(rhob: npt.ArrayLike, rhom: float, rhof: float) -> np.ndarra
         else: 
             phi = (rhom - rhob) / (rhom - rhof)
 
-    phi = correct_range(phi)
+
+    phi = correct_petrophysic_estimation_range(phi)
     return phi
 
     
@@ -91,7 +117,7 @@ def neutron_porosity(nphi: npt.ArrayLike, vsh: npt.ArrayLike,
     else:
         phin = nphi - (vsh * nphi_sh)
 
-    phin = correct_range(phin)
+    phin = correct_petrophysic_estimation_range(phin)
     return phin
 
 
@@ -135,7 +161,7 @@ def neutron_density_porosity(phid: npt.ArrayLike, phin: npt.ArrayLike,
         else:
             phi = np.sqrt( (phid**2 + phin**2) / 2)
 
-    phi = correct_range(phi)
+    phi = correct_petrophysic_estimation_range(phi)
     return phi
 
  
@@ -189,7 +215,7 @@ def sonic_porosity(dt, dtma, dtf):
             phidt = (dt - dtma) / (dtf - dtma)
 
         
-    phidt = correct_range(phidt)
+    phidt = correct_petrophysic_estimation_range(phidt)
     return phidt
 
 
@@ -216,7 +242,7 @@ def gaymard_porosity(phid, phin):
     """
     phie = (0.5 * (phid*phid + phin*phin)) ** 0.5
 
-    phie = correct_range(phie)
+    phie = correct_petrophysic_estimation_range(phie)
     return phie
 
 
@@ -226,7 +252,8 @@ def gaymard_porosity(phid, phin):
     "neutron": neutron_porosity,
     "neutron-density": neutron_density_porosity,
     "sonic": sonic_porosity,
-    "gaymard": gaymard_porosity
+    "gaymard": gaymard_porosity,
+    "effective": effective_porosity
 }
 
 
@@ -239,6 +266,7 @@ def porosity(method: str = "density", **kwargs):
         - neutron-density
         - sonic
         - gaymard
+        - effective
 
     Parameters
     ----------
@@ -251,7 +279,7 @@ def porosity(method: str = "density", **kwargs):
     nphi : array_like
         Neutron log. Required if `method` is "neutron".
     vsh : array_like
-        Total volume of shale in the rock, chosen the most representative. Required if `method` is "neutron".
+        Total volume of shale in the rock, chosen the most representative. Required if `method` is "neutron" or "effective".
     phi_nsh : int, float
         Apparent porosity read in the shales on and under the layer under study and with the same values used in φN. Required if `method` is "neutron".
     dt : array_like
@@ -264,6 +292,8 @@ def porosity(method: str = "density", **kwargs):
         Density porosity (porosity calculated using density log). Required if `method` is "neutron-density" or "gaymard.
     phin : int, float
         Neutron porosity (porosity calculated using neutron log). Required if `method` is "neutron-density" or "gaymard.
+    phi : int, float
+        Total porisity. Required if `method` is "effective".
     method : str, optional
         Name of the method to be used.  Should be one of
             - 'density'
@@ -271,6 +301,7 @@ def porosity(method: str = "density", **kwargs):
             - 'neutron-density'
             - 'sonic'
             - 'gaymard'
+            - 'effective'
         If not given, default method is 'density'
 
     Returns
@@ -292,6 +323,8 @@ def porosity(method: str = "density", **kwargs):
         required = ["dt", "dtma", "dtf"]
     elif method == "gaymard":
         required = ["phid", "phin"]
+    elif method == "effective":
+        required = ["phi", "vsh"]
 
     for arg in required:
         if arg not in kwargs:
diff --git a/stoneforge/petrophysics/shale_volume.py b/stoneforge/petrophysics/shale_volume.py
index 6a09ca1..a89e259 100644
--- a/stoneforge/petrophysics/shale_volume.py
+++ b/stoneforge/petrophysics/shale_volume.py
@@ -1,6 +1,6 @@
 import numpy as np
 import numpy.typing as npt
-
+from stoneforge.petrophysics.helpers import correct_petrophysic_estimation_range
 
 def gammarayindex(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
     """Calculates the gamma ray index.
@@ -49,6 +49,8 @@ def vshale_linear(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray:
 
     """ 
     vshale = gammarayindex(gr, grmin, grmax)
+    vshale = correct_petrophysic_estimation_range(vshale)
+  
 
     return vshale
 
@@ -73,7 +75,7 @@ def vshale_larionov_old(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.nda
     """
     igr = gammarayindex(gr, grmin, grmax)
     vshale = 0.33 * (2. ** (2. * igr) - 1)
-
+    vshale = correct_petrophysic_estimation_range(vshale)
     return vshale
 
 
@@ -97,6 +99,7 @@ def vshale_larionov(gr: npt.ArrayLike, grmin: float, grmax: float) -> np.ndarray
     """
     igr = gammarayindex(gr, grmin, grmax)
     vshale = 0.083 * (2 ** (3.7 * igr) - 1)
+    vshale = correct_petrophysic_estimation_range(vshale)
 
     return vshale
 
@@ -121,6 +124,7 @@ def vshale_clavier(gr: npt.ArrayLike, grmin: float, grmax: float):
     """
     igr = gammarayindex(gr, grmin, grmax)
     vshale = 1.7 - np.sqrt(3.38 - (igr + 0.7) ** 2)
+    vshale = correct_petrophysic_estimation_range(vshale)
 
     return vshale
 
@@ -145,13 +149,14 @@ def vshale_stieber(gr: npt.ArrayLike, grmin: float, grmax: float):
     """
     igr = gammarayindex(gr, grmin, grmax)
     vshale = igr / (3 - 2 * igr)
+    vshale = correct_petrophysic_estimation_range(vshale)
 
     return vshale
 
 
-def vshale_neu_den(neu: npt.ArrayLike, den: npt.ArrayLike, cl1_n: float = -0.15,
-                   cl1_d: float = 2.65, cl2_n: float = 1.00, cl2_d: float = 1.10, clay_n: float = 0.47,
-                   clay_d: float = 2.71) -> np.ndarray:
+def vshale_neu_den(neu: npt.ArrayLike, den: npt.ArrayLike, cl1_n: float,
+                   cl1_d: float, cl2_n: float, cl2_d: float, clay_n: float,
+                   clay_d: float) -> np.ndarray:
     """Estimates the shale volume from neutron and density logs method [1]_.
 
     Parameters
@@ -161,17 +166,17 @@ def vshale_neu_den(neu: npt.ArrayLike, den: npt.ArrayLike, cl1_n: float = -0.15,
     den : array_like
         Bulk density log.
     cl1_n : int, float
-        Neutron porosity value from clean point 1 for empty matrix (NPHI_MATRIX).
+        Neutron porosity value from clean point 1.
     cl1_d : int, float
-        Bulk density value from clean point 1 for empty matrix (RHOB_MATRIX).
+        Bulk density value from clean point 1.
     cl2_n : int, float
-        Neutron porosity value from clean point 2 full porosity.
+        Neutron porosity value from clean point 2.
     cl2_d : int, float
-        Bulk density value from clean point 2 full porosity.
+        Bulk density value from clean point 2.
     clay_n : int, float
-        Neutron porosity value from clay point (NPHI_SHALE).
+        Neutron porosity value from clay point.
     clay_d : int, float
-        Bulk density value from clay point (RHOB_SHALE).
+        Bulk density value from clay point.
 
     Returns
     -------
@@ -190,7 +195,14 @@ def vshale_neu_den(neu: npt.ArrayLike, den: npt.ArrayLike, cl1_n: float = -0.15,
     x3 = (cl2_d - cl1_d) * (clay_n - cl1_n)
     x4 = (clay_d - cl1_d) * (cl2_n - cl1_n)
     vshale = (x1-x2) / (x3-x4)
+    vshale = correct_petrophysic_estimation_range(vshale)
+    return vshale
 
+def vshale_nrm(phit: npt.ArrayLike, phie: npt.ArrayLike):
+
+    cbw = phie - phit
+    vshale = cbw / phit
+    vshale = correct_petrophysic_estimation_range(vshale)
     return vshale
 
 
@@ -245,3 +257,5 @@ def vshale(gr: npt.ArrayLike, grmin: float, grmax: float, method: str = None) ->
     fun = _vshale_methods[method]
 
     return fun(gr, grmin, grmax)
+
+
diff --git a/stoneforge/petrophysics/water_saturation.py b/stoneforge/petrophysics/water_saturation.py
index 62a1c48..8208d83 100644
--- a/stoneforge/petrophysics/water_saturation.py
+++ b/stoneforge/petrophysics/water_saturation.py
@@ -1,39 +1,31 @@
 import numpy as np
 import numpy.typing as npt
 import warnings
+from stoneforge.petrophysics.helpers import correct_petrophysic_estimation_range
+
 
 # Make anomalous water saturation values larger than 1 be one
 def correct_range(sw: np.ndarray):
     sw[sw > 1] = 1
     return sw
 
-
-
-def check_saturation_range(sw: np.ndarray):
-    if np.any(sw > 1):
-        warnings.warn(UserWarning("Water saturation must be a value between 0 and 1."))
-    elif np.any(sw < 0):
-        warnings.warn(UserWarning("Water saturation must be a positive value."))
-    
-
-
 def archie(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
            m: float, n: float) -> np.ndarray:
     """Estimate the Water Saturation from Archie's [1]_ equation.
 
     Parameters
     ----------
-    rw : float
+    rw : int, float
         Water resistivity.  
     rt : array_like
         Formation resistivity.    
     phi : array_like
         Porosity.   
-    a : float
+    a : int, float
         Tortuosity factor.
-    m : float
+    m : int, float
         Cementation exponent.
-    n : float
+    n : int, float
         Saturation exponent.
 
     Returns
@@ -47,15 +39,16 @@ def archie(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
     reservoir characteristics. Transactions of the AIME, 146(01), 54-62.
 
     """
-    sw = ((a * rw) / ((phi ** m) * rt)) ** (1/n)
-
-    check_saturation_range(sw)
-
-    sw = correct_range(sw)
-
-    return sw
-
+    if any(((a*rw) / (phi**m * rt))**(1/n) > 1):
+        warnings.warn(UserWarning("saturation of water must be a value between 0 and 1"))
+        sw = ((a*rw) / (phi**m * rt))**(1/n)
+        sw = correct_petrophysic_estimation_range(sw)
+        return sw
 
+    else:
+        sw = ((a*rw) / (phi**m * rt))**(1/n)
+        sw = correct_petrophysic_estimation_range(sw)
+        return sw
 
 
 def simandoux(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
@@ -98,11 +91,8 @@ def simandoux(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
     D = C * vsh / (2*rsh)
     E = C / rt
     sw = ((D**2 + E)**0.5 - D)**(2/n)
- 
-    check_saturation_range(sw)
 
-    sw = correct_range(sw)
-   
+    sw = correct_petrophysic_estimation_range(sw)
 
 
     return sw
@@ -144,11 +134,8 @@ def indonesia(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
 
     """
     sw = ((1/rt)**0.5 / ((vsh**(1 - 0.5*vsh) / (rsh)**0.5) + (phi**m / a*rw)**0.5))**(2/n)
-    check_saturation_range(sw)
+    sw = correct_petrophysic_estimation_range(sw)
 
-    sw = correct_range(sw)
-
-    
 
     return sw
 
@@ -186,9 +173,7 @@ def fertl(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike, a: float,
 
     """
     sw = phi**(-m/2) * ((a*rw/rt + (alpha*vsh/2)**2)**0.5 - (alpha*vsh/2))
-    check_saturation_range(sw)
-
-    sw = correct_range(sw)
+    sw = correct_petrophysic_estimation_range(sw)
 
 
     return sw
@@ -269,6 +254,7 @@ def water_saturation(rw: float, rt: npt.ArrayLike, phi: npt.ArrayLike,
     
     fun = _sw_methods[method]
 
+
     sw = fun(rw, rt, phi, a, m, **options)
-    sw = correct_range(sw)
+    
     return sw
diff --git a/stoneforge/preprocessing/__init__.py b/stoneforge/preprocessing/__init__.py
index b220232..59a049a 100644
--- a/stoneforge/preprocessing/__init__.py
+++ b/stoneforge/preprocessing/__init__.py
@@ -2,4 +2,5 @@
 from .data_management import project
 from .data_processing import well_train_test_split
 from .data_processing import data_assemble
-from .data_processing import predict_processing
\ No newline at end of file
+from .data_processing import predict_processing
+from . import las2  # noqa: F401
\ No newline at end of file
diff --git a/stoneforge/preprocessing/data_management.py b/stoneforge/preprocessing/data_management.py
index 57414d3..5726397 100644
--- a/stoneforge/preprocessing/data_management.py
+++ b/stoneforge/preprocessing/data_management.py
@@ -3,6 +3,7 @@
 import pickle
 import json
 import os
+import pandas
 
 from . import las2
 
@@ -113,6 +114,7 @@ def convert_into_matrix(self,reference_mnemonics=False):
                 well_data = self.well_data[i]
 
             for j in well_data:
+                # print(i,j) - search for wells mnemonics
                 data.append(self.well_data[i][j]['data'])
                 units.append(self.well_data[i][j]['unit'])
                 mnemonics.append(j)
@@ -172,9 +174,12 @@ def shape_check(self,ref):
         for i in self.well_data:
             if np.shape(self.well_data[i]['data'])[0] == value:
                 well_data[i] = self.well_data[i]
+            else:
+                print("well: '{}'".format(i),"because it has less logs")
 
         self.well_data = well_data
 
+    # ============================================ #
         
 
 
diff --git a/stoneforge/preprocessing/data_processing.py b/stoneforge/preprocessing/data_processing.py
index 6641cb4..7c4c211 100644
--- a/stoneforge/preprocessing/data_processing.py
+++ b/stoneforge/preprocessing/data_processing.py
@@ -1,5 +1,3 @@
-
-
 from sklearn.model_selection import train_test_split
 import numpy as np
 
@@ -11,6 +9,7 @@ def __init__(self,data,data_key):
         self.idx = {}
         self.clean_data = {}
 
+
     def _nan_idx(self):
 
         for i in self.data:
@@ -20,15 +19,18 @@ def _nan_idx(self):
                     local.append(j)
             self.idx[i] = local
 
+
     def matrix_values(self):
         self._nan_idx()
 
         clean_data = {}
         for i in self.data:
-           clean_data[i] = _remove_dummies(self.data[i][self.data_key])
+           
+           clean_data[i] = self._remove_dummies(self.data[i][self.data_key])
 
         return clean_data
 
+
     def return_curve(self,y):
 
         curves = {}
@@ -42,6 +44,25 @@ def return_curve(self,y):
             curves[i] = curve
 
         return curves
+    
+
+    def train_test_split(self, X, y, test_size = 0.30, random_state = 99):
+
+        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=random_state)
+        curves = {
+            "X_train":X_train,
+            "X_test":X_test,
+            "y_train":y_train,
+            "y_test":y_test
+        }
+        return curves
+
+    
+    def _remove_dummies(self,data):
+        data_1 = np.array(data).T
+        data_2 = data_1[~np.isnan(data_1).any(axis=1)]
+
+        return data_2
 
     def train_test_split(self, X, y, test_size = 0.30, random_state = 99):
 
diff --git a/stoneforge/pseudo_wells/__init__.py b/stoneforge/pseudo_wells/__init__.py
index 977e97d..f72e2f7 100644
--- a/stoneforge/pseudo_wells/__init__.py
+++ b/stoneforge/pseudo_wells/__init__.py
@@ -1,1 +1,1 @@
-from . import monte_carlo_simulations  # noqa: F401
+from . import monte_carlo_simulations  # noqa: F401
\ No newline at end of file
diff --git a/stoneforge/rock_physics/elastic_constants.py b/stoneforge/rock_physics/elastic_constants.py
index 0533bc8..aabedde 100644
--- a/stoneforge/rock_physics/elastic_constants.py
+++ b/stoneforge/rock_physics/elastic_constants.py
@@ -184,9 +184,6 @@ def compressional_modulus(rhob: npt.ArrayLike, vp: npt.ArrayLike):
 
     return M
 
-                          
-
-
 def poisson(method: str, **kwargs):
     """Computes the Poisson ratio using two elastic moduli.
 
diff --git a/stoneforge/rock_physics/fluid_substitution.py b/stoneforge/rock_physics/fluid_substitution.py
index c53b735..7d5cec9 100644
--- a/stoneforge/rock_physics/fluid_substitution.py
+++ b/stoneforge/rock_physics/fluid_substitution.py
@@ -1,6 +1,5 @@
 import numpy as np
 import numpy.typing as npt
-import warnings
 
 
 def kdry(phi: npt.ArrayLike, ks: npt.ArrayLike, ksatA: npt.ArrayLike,
@@ -111,10 +110,6 @@ def gassmann_subs(phi: npt.ArrayLike, ks: npt.ArrayLike, ksatA: npt.ArrayLike,
 
     """
     A = ksatA / (ks - ksatA)
-
-
- 
-
     B = kfluidA / (phi*(ks - kfluidA))
     C = kfluidB / (phi*(ks - kfluidB))
     D = A - B + C
@@ -131,7 +126,7 @@ def gassmann_subs(phi: npt.ArrayLike, ks: npt.ArrayLike, ksatA: npt.ArrayLike,
 
 
 def gassmann(phi: npt.ArrayLike, ks: npt.ArrayLike,
-             method: str = "gassmann_subs", **kwargs) -> np.ndarray:
+             method: str = "ksat_direct", **kwargs) -> np.ndarray:
     """Compute Gassmann' equations.
 
     This is a façade for the methods:
@@ -313,7 +308,7 @@ def mavko_subs(phi: npt.ArrayLike, ms: npt.ArrayLike, msatA: npt.ArrayLike,
 
 
 def mavko(phi: npt.ArrayLike, ms: npt.ArrayLike,
-             method: str = "mavko_subs", **kwargs) -> np.ndarray:
+             method: str = "msat_direct", **kwargs) -> np.ndarray:
     """Compute Mavko' equations.
 
     This is a façade for the methods:
diff --git a/stoneforge/rock_physics/inclusion.py b/stoneforge/rock_physics/inclusion.py
index e81f119..7be3965 100644
--- a/stoneforge/rock_physics/inclusion.py
+++ b/stoneforge/rock_physics/inclusion.py
@@ -1,20 +1,22 @@
 """
 From Berryman 1980
 """
-
+import numpy.typing as npt
+import warnings
 import numpy as np
 from scipy.optimize import fsolve
+from stoneforge.rock_physics.elastic_constants import poisson
 
-def theta(alpha):
+def get_theta(alpha):
     return alpha*(np.arccos(alpha) - alpha*np.sqrt(1.0 - alpha*alpha))/(1.0 - alpha*alpha)**(3.0/2.0)
 
-def f(alpha, theta):
-    return alpha*alpha*(3.0*theta - 2.0)/(1.0 - alpha*alpha)
+def get_f(alpha, theta):
+    return (alpha*alpha*(3.0*theta - 2.0))/(1.0 - alpha*alpha)
 
 def PQ(A, B, R, theta, f):
     F1 = 1.0 + A*(1.5*(f + theta) - R*(1.5*f + 2.5*theta - 4.0/3.0))
     F2 = 1.0 + A*(1.0 + 1.5*(f + theta) - R*(1.5*f + 2.5*theta)) + B*(3.0 - 4.0*R) + A*(A + 3.0*B)*(1.5 - 2.0*R)*(f + theta - R*(f - theta + 2.0*theta*theta))
-    F3 = 1.0 + A*(1.0 - f - 1.5*theta + R*(f + theta))
+    F3 = 1.0 + A*(1.0 - (f + 1.5*theta) + R*(f + theta))
     F4 = 1.0 + (A/4.0)*(f + 3.0*theta - R*(f - theta))
     F5 = A*(-f + R*(f + theta - 4.0/3.0)) + B*theta*(3.0 - 4.0*R)
     F6 = 1.0 + A*(1.0 + f - R*(f + theta)) + B*(1.0 - theta)*(3.0 - 4.0*R)
@@ -22,55 +24,77 @@ def PQ(A, B, R, theta, f):
     F8 = A*(1.0 - 2.0*R + (f/2.0)*(R - 1.0) + (theta/2.0)*(5.0*R - 3.0)) + B*(1.0 - theta)*(3.0 - 4.0*R)
     F9 = A*((R - 1.0)*f - R*theta) + B*theta*(3.0 - 4.0*R)
     
-    P = 3.0*F1/F2
-    Q = 2.0/F3 + 1.0/F4 + (F4*F5 + F6*F7 - F8*F9)/(F2*F4)
+    P = F1/F2
+    Q = (2.0/F3 + 1.0/F4 + ((F4*F5 + F6*F7 - F8*F9)/(F2*F4)))/5.0
     return P, Q
 
-def KG(Km, Gm, Ki, Gi, ci, theta, f):
-    A = Gi/Gm - 1.0
-    B = (Ki/Km - Gi/Gm)/3.0
-    R = Gm/(Km + (4.0/3.0)*Gm)
-    Fm = (Gm/6.0)*(9.0*Km + 8.0*Gm)/(Km + 2.0*Gm)
+def ABR(k, g, ks, gs):
+    vsol = poisson(method='k_and_g', **{"k": ks, "g": gs})
+    A = (g/gs) - 1.0
+    B = ((k/ks) - (g/gs))/3.0
+    R = (1 - (2*vsol))/(2 - (2*vsol))
+    return A, B, R
+
+
+
+def Kuster_Toksöz(phi: npt.ArrayLike, ks: npt.ArrayLike, gs: npt.ArrayLike, k: float, g: float, alpha: float):
+    """
+    Calculate bulk modulus and shear modulus using Kuster-Toksöz equation .
+
+    Parameters
+    ----------
+    phi : array_like
+        Porosity log.
+
+    ks : array_like
+        Bulk modulus of solid phase.
+
+    gs : array_like
+        Shear modulus of solid phase.
+
+    k : float
+        Inclusion bulk modulus.
+
+    g : float
+        Inclusion shear modulus.
+
+    alpha : float
+        Inclusion aspect ratios.
+
+    Returns
+    -------
+    k_kt : array_like
+        Bulk modulus.
+    g_kt : array_like
+        Shear modulus.
+
+    References
+    ----------
+    .. [1] Dvorkin, J.; Gutierrez, M. A.; Grana, D. Seismic reflections of rock
+    properties. [S.l.]: Cambridge University Press, 2014.
+
+    """
     
+    theta = get_theta(alpha)
+    f = get_f(alpha, theta)
+    A, B, R = ABR(k, g, ks, gs)
     P, Q = PQ(A, B, R, theta, f)
 
-    K = Km - (Km + (4.0/3.0)*Gm)*ci*(Km - Ki)*P/3.0/(Km + (4.0/3.0)*Gm + ci*(Km - Ki)*P/3.0)
-    G = Gm - (Gm + Fm)*ci*(Gm - Gi)*Q/5.0/(Gm + Fm + ci*(Gm - Gi)*Q/5.0)
-    
+    Fm = (9.0*ks + 8.0*gs)/(ks + 2.0*gs)
+    kr = (k - ks)*(phi*P)
+    x = (3*kr)/(3*ks + 4*gs)
+    numerator = ((4/3)*(gs*x)) + ks
+    denominator = (1-x)
+    K = numerator / denominator
+   
+ 
+  
+    #K = ks - (ks + (4.0/3.0)*gs)*phi*(ks - k)*P/3.0/(ks + (4.0/3.0)*gs + phi*(ks - k)*P/3.0)
+    G = gs - (gs + Fm)*phi*(gs - g)*Q/5.0/(gs + Fm + phi*(gs - g)*Q/5.0)
+
+
+   
+
     return K, G
+    
 
-def DEM(Km, Gm, Ki, Gi, alphai, phii, phi0=0.0, r=1000, phitol=1.0E-10, gamma=0.01):
-    phi = np.sum(phii)
-    fraci = phii/np.sum(phi)
-    ci = fraci*alphai/r
-    n = int(np.ceil((np.log(1.0-phi)-np.log(1.0-phi0))/np.sum(np.log(1.0-ci))))
-    m = len(alphai)
-
-# Matrix properties
-Km = 77.0 #GPa
-Gm = 32.0 #Gpa
-rhom = 2.71
-
-# Fluid properties
-Kf = 3.0
-rhof = 1.0
-
-# Porosity
-phimax = 0.4
-
-# Inclusion properties
-# In this example a mixture of three inclusion types are used:
-# - 30% of 0.02 aspect ratio
-# - 50% of 0.15 aspect ratio
-# - 20% of 0.80 aspect ratio
-alphas = np.array([0.01, 0.15, 0.8])
-volumes = np.array([0.3, 0.5, 0.2])*phimax
-
-# Dry inclusions
-Kis = np.zeros(len(alphas), dtype=float)
-Gis = np.zeros(len(alphas), dtype=float)
-
-# The DEM function returns the bulk and shear moduli along with the porosity array to match them.
-# The porosity array is not regularly spaced. If you need so, you should reinterpolate
-K, G, phi = DEM(Km, Gm, Kis, Gis, alphas, volumes)
-print('K', K, 'len(K)', len(K), G, phi)
\ No newline at end of file
diff --git a/stoneforge/tvdss/__init__.py b/stoneforge/tvdss/__init__.py
deleted file mode 100644
index e3baa7e..0000000
--- a/stoneforge/tvdss/__init__.py
+++ /dev/null
@@ -1,1 +0,0 @@
-from . import calculate_tvdss  # noqa: F401
\ No newline at end of file
diff --git a/stoneforge/tvdss/calculate_tvdss.py b/stoneforge/tvdss/calculate_tvdss.py
deleted file mode 100644
index 4d53ee8..0000000
--- a/stoneforge/tvdss/calculate_tvdss.py
+++ /dev/null
@@ -1,17 +0,0 @@
-
-def correct_step_value(correction_parameter, depth_step):
-        return correction_parameter - depth_step
-def round_values(depth_step):
-       return round(depth_step, 4)
-
-
-def get_tvdss(measured_depth_data, rotary_table, topography_or_water_blade):
-
-    if topography_or_water_blade is not None:
-        correction_parameter = rotary_table + topography_or_water_blade
-    else:
-        correction_parameter = rotary_table
-    tvdss_data = [correct_step_value(correction_parameter, i) for i in measured_depth_data]
-    tvdss_data = [round_values(i) for i in tvdss_data]
-
-    return tvdss_data
diff --git a/stoneforge/wavelets/__init__.py b/stoneforge/wavelets/__init__.py
new file mode 100644
index 0000000..c9b595d
--- /dev/null
+++ b/stoneforge/wavelets/__init__.py
@@ -0,0 +1,3 @@
+from . import butterworth  # noqa: F401
+from . import ricker  # noqa: F401
+from . import ormsby  # noqa: F401
diff --git a/stoneforge/wavelets/butterworth.py b/stoneforge/wavelets/butterworth.py
new file mode 100644
index 0000000..9e35679
--- /dev/null
+++ b/stoneforge/wavelets/butterworth.py
@@ -0,0 +1,51 @@
+import warnings
+from typing import Callable, Optional, Sequence, Tuple
+
+from scipy import signal
+import numpy as np
+import numpy.typing as npt
+
+import matplotlib.pyplot as plt
+
+def _tcrop(t: npt.ArrayLike) -> npt.ArrayLike:
+    """Crop time axis with even number of samples"""
+    if len(t) % 2 == 0:
+        t = t[:-1]
+        warnings.warn("one sample removed from time axis...")
+    return t
+
+
+def Butter_Wavelet(Freq_low: float = 1.5,
+                   Freq_hi: float = 65,
+                   Samples: int = 71,
+                   Dt: float = 4) -> Tuple[npt.ArrayLike, npt.ArrayLike]:
+
+    r"""Butterworth wavelet
+    Create a Butterworth wavelet given time axis ``t``, minimum frequeny and maximun frequency
+    Parameters
+    ----------
+    Freq_low : :obj:`float`, optional
+        Minimun frequency
+    Freq_hi : :obj:`float`, optional
+        Maximun frequency
+    Samples : :float
+        Number of samples       
+    Dt : :float
+        Sampling in milisseconds
+    Returns
+    -------
+    wav : :obj:`numpy.ndarray`
+        Wavelet
+    t : :obj:`numpy.ndarray`
+        Symmetric time axis
+    """
+
+    t = np.arange(Samples)*(Dt/1000)
+    t = _tcrop(t)
+    t = np.concatenate((np.flipud(-t[1:]), t), axis=0)
+    imp = signal.unit_impulse(t.shape[0], 'mid')
+    b, a = signal.butter(4, Freq_hi,fs = 1000*(1/Dt))
+    response_zp = signal.filtfilt(b, a, imp)
+    low_b, low_a = signal.butter(2,Freq_low,'hp', fs = 1000*(1/Dt))
+    wav = signal.filtfilt(low_b, low_a, response_zp)
+    return t, wav
diff --git a/stoneforge/wavelets/ormsby.py b/stoneforge/wavelets/ormsby.py
new file mode 100644
index 0000000..86ac63e
--- /dev/null
+++ b/stoneforge/wavelets/ormsby.py
@@ -0,0 +1,55 @@
+
+import warnings
+from typing import Sequence, Tuple
+
+import numpy as np
+import numpy.typing as npt
+
+import matplotlib.pyplot as plt
+
+
+def _tcrop(t: npt.ArrayLike) -> npt.ArrayLike:
+    """Crop time axis with even number of samples"""
+    if len(t) % 2 == 0:
+        t = t[:-1]
+        warnings.warn("one sample removed from time axis...")
+    return t
+
+def getOrmsby(f: Sequence[float] = (5,10,40,50),
+              Samples: float = 71, 
+              Dt: float = 4) -> Tuple[npt.ArrayLike, npt.ArrayLike]:
+    r"""Ormsby wavelet
+    Create a Ormsby wavelet given time axis ``t`` and frequency range
+    defined by four frequencies which parametrize a trapezoidal shape in
+    the frequency spectrum.
+    Parameters
+    ----------
+    f : :obj:`tuple`, optional
+        Frequency range
+    Samples : :obj:`float`, optional
+        Number of samples       
+    Dt : obj:`float`, optional
+        Sampling in milisseconds
+    Returns
+    -------
+    wav : :obj:`numpy.ndarray`
+        Wavelet
+    t : :obj:`numpy.ndarray`
+        Symmetric time axis
+    """
+    assert len(f) == 4, 'Ormsby wavelet needs 4 frequencies as input'
+    f = np.sort(f) #Ormsby wavelet frequencies must be in increasing order
+    t = np.arange(Samples)*(Dt/1000)
+    t = _tcrop(t)
+    t = np.concatenate((np.flipud(-t[1:]), t), axis=0)
+    pif   = np.pi*f
+    den1  = pif[3] - pif[2]
+    den2  = pif[1] - pif[0]
+    term1 = (pif[3]*np.sinc(f[3]*t))**2 - (pif[2]*np.sinc(f[2]*t))**2
+    term2 = (pif[1]*np.sinc(f[1]*t))**2 - (pif[0]*np.sinc(f[0]*t))**2
+
+    wav   = term1/den1 - term2/den2;
+    wav /= np.amax(wav)
+    return t, wav
+
+
diff --git a/stoneforge/wavelets/ricker.py b/stoneforge/wavelets/ricker.py
new file mode 100644
index 0000000..54d4b3f
--- /dev/null
+++ b/stoneforge/wavelets/ricker.py
@@ -0,0 +1,43 @@
+
+import warnings
+from typing import Callable, Optional, Sequence, Tuple
+
+import numpy as np
+import numpy.typing as npt
+
+import matplotlib.pyplot as plt
+
+
+def _tcrop(t: npt.ArrayLike) -> npt.ArrayLike:
+    """Crop time axis with even number of samples"""
+    if len(t) % 2 == 0:
+        t = t[:-1]
+        warnings.warn("one sample removed from time axis...")
+    return t
+
+def Ricker_Wavelet(Peak_freq: float = 30,
+                   Samples: float = 71,
+                   Dt: float = 4) -> Tuple[npt.ArrayLike, npt.ArrayLike]:
+    r"""Ricker wavelet
+    Create a Ricker wavelet given time axis ``t`` and central frequency ``f_0``
+    Parameters
+    ----------
+    Peak_freq : :obj:`float`, optional
+        Central frequency
+    Samples : :obj:`float`, optional
+        Number of samples
+    Dt : :obj:`func`, optional
+        Sampling in milisseconds
+    Returns
+    -------
+    ricker : :obj:`numpy.ndarray`
+        Wavelet
+    t : :obj:`numpy.ndarray`
+        Symmetric time axis
+    
+    """
+    t = np.arange(Samples)*(Dt/1000)
+    t = _tcrop(t)
+    t = np.concatenate((np.flipud(-t[1:]), t), axis=0)
+    ricker = (1. -2.*(np.pi**2)*(Peak_freq**2)*(t**2))*np.exp(-(np.pi**2)*(Peak_freq**2)*(t**2))
+    return t, ricker
\ No newline at end of file


Test patch:
diff --git a/stoneforge/rock_physics/tests/test_fluid_substitution.py b/stoneforge/rock_physics/tests/test_fluid_substitution.py
new file mode 100644
index 0000000..74affcb
--- /dev/null
+++ b/stoneforge/rock_physics/tests/test_fluid_substitution.py
@@ -0,0 +1,24 @@
+import sys
+import os
+
+
+if __package__:
+    from ..fluid_substitution import gassmann
+else:
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    from fluid_substitution import gassmann
+
+
+def test_kdry():
+    assert round(gassmann(phi=0.2, ks=36, ksatA=17.6, kfluidA=3.013,
+                          method="kdry"), 1) == 12.
+
+
+def test_ksat():
+    assert round(gassmann(phi=0.2, ks=36, kdry=12, kfluidB=3.013,
+                          method="ksat"), 1) == 17.6
+
+
+def test_gassmann_subs():
+    assert round(gassmann(phi=0.2, ks=36, ksatA=12.29, kfluidA=0.133,
+                 kfluidB=3.013, method="gassmann_subs"), 1) == 17.6
diff --git a/stoneforge/tests/tests_ml/LabelEncoded.pkl b/stoneforge/tests/tests_ml/LabelEncoded.pkl
new file mode 100644
index 0000000..819a30b
Binary files /dev/null and b/stoneforge/tests/tests_ml/LabelEncoded.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/LabelEncoded.pkl b/stoneforge/tests/tests_ml/_ml_project/LabelEncoded.pkl
new file mode 100644
index 0000000..c6f56a8
Binary files /dev/null and b/stoneforge/tests/tests_ml/_ml_project/LabelEncoded.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/all_methods.json b/stoneforge/tests/tests_ml/_ml_project/all_methods.json
new file mode 100644
index 0000000..369f287
--- /dev/null
+++ b/stoneforge/tests/tests_ml/_ml_project/all_methods.json
@@ -0,0 +1,1 @@
+["decision_tree_regression", "suporte_vector_regression", "linear_regression", "random_forest_regression", "lightgbm_regression", "xgboost_regressioncatboost_regression"]
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/_ml_project/linear_regression_fit_property.pkl b/stoneforge/tests/tests_ml/_ml_project/linear_regression_fit_property.pkl
new file mode 100644
index 0000000..12e40c1
Binary files /dev/null and b/stoneforge/tests/tests_ml/_ml_project/linear_regression_fit_property.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/linear_regression_settings.json b/stoneforge/tests/tests_ml/_ml_project/linear_regression_settings.json
new file mode 100644
index 0000000..9e26dfe
--- /dev/null
+++ b/stoneforge/tests/tests_ml/_ml_project/linear_regression_settings.json
@@ -0,0 +1,1 @@
+{}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/_ml_project/polinomial_settings.json b/stoneforge/tests/tests_ml/_ml_project/polinomial_settings.json
new file mode 100644
index 0000000..ff910d9
--- /dev/null
+++ b/stoneforge/tests/tests_ml/_ml_project/polinomial_settings.json
@@ -0,0 +1,1 @@
+{"degree": 1}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/_ml_project/scaler.pkl b/stoneforge/tests/tests_ml/_ml_project/scaler.pkl
new file mode 100644
index 0000000..ae674ef
Binary files /dev/null and b/stoneforge/tests/tests_ml/_ml_project/scaler.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/scalerp.pkl b/stoneforge/tests/tests_ml/_ml_project/scalerp.pkl
new file mode 100644
index 0000000..e6852dd
Binary files /dev/null and b/stoneforge/tests/tests_ml/_ml_project/scalerp.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/xgboost_fit_property.pkl b/stoneforge/tests/tests_ml/_ml_project/xgboost_fit_property.pkl
new file mode 100644
index 0000000..d3f97fe
Binary files /dev/null and b/stoneforge/tests/tests_ml/_ml_project/xgboost_fit_property.pkl differ
diff --git a/stoneforge/tests/tests_ml/_ml_project/xgboost_regression_settings.json b/stoneforge/tests/tests_ml/_ml_project/xgboost_regression_settings.json
new file mode 100644
index 0000000..9e26dfe
--- /dev/null
+++ b/stoneforge/tests/tests_ml/_ml_project/xgboost_regression_settings.json
@@ -0,0 +1,1 @@
+{}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/all_methods.json b/stoneforge/tests/tests_ml/all_methods.json
new file mode 100644
index 0000000..369f287
--- /dev/null
+++ b/stoneforge/tests/tests_ml/all_methods.json
@@ -0,0 +1,1 @@
+["decision_tree_regression", "suporte_vector_regression", "linear_regression", "random_forest_regression", "lightgbm_regression", "xgboost_regressioncatboost_regression"]
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/all_methods_test.py b/stoneforge/tests/tests_ml/all_methods_test.py
new file mode 100644
index 0000000..dccafac
--- /dev/null
+++ b/stoneforge/tests/tests_ml/all_methods_test.py
@@ -0,0 +1,203 @@
+# %%
+
+import numpy as np
+import sys
+import os
+import pandas 
+
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+
+if __package__:
+    from ..machine_learning import *
+else:
+    print('passed ml')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import machine_learning
+
+if __package__:
+    from ..preprocessing import *
+else:
+    print('passed mgt')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import preprocessing
+
+# %%
+
+#project = preprocessing.project("D:\\appy_projetos\\wells")
+project = preprocessing.project("C:\\Users\\joseaugustodias\\Desktop\\pocos")
+project.import_folder()
+project.import_several_wells()
+
+print(project.well_names_paths)
+
+#Na proxima janela tem que aparecer o histograma
+#%%
+
+mnemonics_replacement = {
+    'DEPTH':['DEPTH'],
+    'GR':['GR'],
+    'CAL':['CAL','DCAL','HCAL','CALI'],
+    'RHOB':["RHOB","RHOZ","RHLA","RHBA","RHLA3","RHBA4"],
+    'RES':["ILD","HDRS","RT","AHT901","AT90","RT90"],
+    'NPHI':['NPHI'],
+    'Lithology':['Lith_new']
+}
+
+ref_mnemonics = list(mnemonics_replacement.keys())
+
+project.data_replacement(mnemonics_replacement)
+project.convert_into_matrix(ref_mnemonics)
+
+#Histograma
+# %%
+
+b = np.delete(project.well_data['7-MP-33D-BA']['data'], -2, axis=0)
+print(b,np.shape(b))
+
+mnem = ['DEPTH', 'GR', 'CAL', 'RES', 'RHOB']
+unit = ['M', 'gAPI', 'in', 'ohm.m', 'g/cm3']
+
+project.well_data['test'] = {}
+
+project.well_data['test']['data'] = b
+project.well_data['test']['units'] = unit
+project.well_data['test']['mnemonics'] = mnem
+
+project.shape_check(mnemonics_replacement)
+
+# %%
+#Tamanho teste x treino 
+
+tw_data,vw_data = preprocessing.well_train_test_split(['7-MP-22-BA','7-MP-50D-BA'],project.well_data)
+
+mega_data = preprocessing.data_assemble(tw_data,'data')
+print(np.shape(mega_data))
+
+# %%
+
+print(ref_mnemonics)
+
+def _remove_dummies(data):
+    data_1 = np.array(data).T
+    data_2 = data_1[~np.isnan(data_1).any(axis=1)]
+
+    return data_2
+
+mega_data = _remove_dummies(mega_data)
+
+print(np.shape(mega_data))
+#print(vw_data['7-MP-22-BA']['data'])
+
+# %%
+#Opção se vai querer ou não fazer a redimensionamento do dado
+
+from sklearn.preprocessing import LabelEncoder
+
+y = mega_data[:,-1]
+X = np.delete(mega_data,(-1), axis=1)
+#X = np.array(X, dtype='float')
+#y = np.array(y, dtype='int')
+
+y1 = [49., 25., 54., 57., 49.]
+y2 = [25., 54., 57., 49.]
+y3 = [25., 57., 49.]
+
+tr3 = [0, 3, 1]
+#tr3 = [0, 2, 1]
+
+le = LabelEncoder()
+print(le.fit_transform(y1))
+print(le.fit_transform(y2))
+print(le.fit_transform(y3))
+print(le.fit_transform(tr3))
+
+
+# %%
+#Aqui o usuario precisa escolher 1. Escolher o métodos, 2. se ele vai querer utilizar o pseudo automatização; 3.Se não quiser, ajustar os parametros que ele quer utlizar
+machine_learning.settings(method = "GaussianNB", path='_ml_project')
+machine_learning.settings(method = "DecisionTreeClassifier", path='_ml_project',max_depth = 3, criterion = 'gini')
+#machine_learning.settings(method = "SVM", path='_ml_project')
+#machine_learning.settings(method = "LogisticRegression", path='_ml_project')
+machine_learning.settings(method = "KNeighborsClassifier", path='_ml_project', n_neighbors = np.arange(3,61,2), weights = uniform , p = np.arange(1,6))
+#achine_learning.settings(method = "RandomForestClassifier", path='_ml_project', n_estimators =  100, learning_rate = 0.5, max_depth =  5 )
+#machine_learning.settings(method = "XGBClassifier", path='_ml_project', n_estimators =  100, learning_rate = 0.5, max_depth =  5 ))
+#machine_learning.settings(method = "CatBoostClassifier", path='_ml_project')
+
+
+# %%
+
+a = preprocessing.predict_processing(vw_data,'data')
+x_r = a.matrix_values()
+
+y_vdb = {}
+x_db = {}
+for i in x_r:
+    y_vdb[i] = x_r[i][:,-1]
+    x_db[i] = np.delete(x_r[i],(-1), axis=1)
+
+# %%
+#Rodar o metodo
+
+#machine_learning.fit(X,y,method = "GaussianNB", path = "_ml_project")
+machine_learning.fit(X,y,method = "DecisionTreeClassifier", path = "_ml_project")
+#machine_learning.fit(X,y,method = "SVM", path = "_ml_project")
+#machine_learning.fit(X,y,method = "LogisticRegression", path = "_ml_project")
+#machine_learning.fit(X,y,method = "KNeighborsClassifier", gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "RandomForestClassifier", gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "XGBClassifier",gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "CatBoostClassifier",gs = True, path = "_ml_project")
+
+
+# %%
+
+class_db = {}
+
+for x in x_db:
+    #class_db[x] = machine_learning.predict(x_db[x], method = "GaussianNB", path = "_ml_project")
+    class_db[x] = machine_learning.predict(x_db[x], method = "DecisionTreeClassifier", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "SVM", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "LogisticRegression", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "KNeighborsClassifier", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "RandomForestClassifier", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "XGBClassifier", path = "_ml_project")
+    #class_db[x] = machine_learning.predict(x_db[x], method = "CatBoostClassifier", path = "_ml_project")
+
+
+a.return_curve(class_db)
+
+
+
+# %%
+
+machine_learning.settings(method = "GaussianNB")
+machine_learning.fit(X,y,method = "GaussianNB")
+
+for x in x_db:
+    class_db[x] = machine_learning.predict(x_db[x], method = "GaussianNB")
+    
+
+# %%
+
+print(y,len(y))
+
+# %%
+
+class_db['7-MP-50D-BA']
+
+# %%
+
+aa = a.return_curve(class_db)
+
+print(class_db['7-MP-22-BA'],len(class_db['7-MP-22-BA']))
+print(y_vdb['7-MP-22-BA'],len(y_vdb['7-MP-22-BA']))
+# %%
+
+a = 0
+for i in range(len(class_db['7-MP-22-BA'])):
+    if class_db['7-MP-22-BA'][i] == y_vdb['7-MP-22-BA'][i]:
+        a += 1
+
+print(a)
+
+# %%
diff --git a/stoneforge/tests/tests_ml/all_methods_test_classification.py b/stoneforge/tests/tests_ml/all_methods_test_classification.py
new file mode 100644
index 0000000..ea6debf
--- /dev/null
+++ b/stoneforge/tests/tests_ml/all_methods_test_classification.py
@@ -0,0 +1,202 @@
+# %%
+
+import numpy as np
+import sys
+import os
+import pandas 
+
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+
+if __package__:
+    from ..machine_learning import *
+else:
+    print('passed ml')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import machine_learning
+
+if __package__:
+    from ..preprocessing import *
+else:
+    print('passed mgt')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import preprocessing
+
+# %%
+project = preprocessing.project("Y:\\appy_dados\\wells_es")
+#project = preprocessing.project("C:\\Users\\joseaugustodias\\Desktop\\pocos")
+project.import_folder()
+project.import_several_wells()
+
+print(project.well_names_paths)
+
+#%%
+
+mnemonics_replacement = {
+    'DEPTH':['DEPTH',"MD"],
+    'GR':['GR'],
+    'CAL':['CAL','DCAL','HCAL','CALI'],
+    'RHOB':["RHOB","RHLA","RHBA","RHLA3","RHBA4"],
+    'RES':["ILD","LLD","HDRS","RT","AHT901","AT90","RT90"],
+    'DT':["DTCO","DT"],
+    'NPHI':['NPHI'],
+    'Lithology':['LITO']
+}
+
+ref_mnemonics = list(mnemonics_replacement.keys())
+
+project.data_replacement(mnemonics_replacement)
+project.convert_into_matrix(ref_mnemonics)
+
+# %%
+
+well_test = np.delete(project.well_data['7-MP-33D-BA']['data'], -2, axis=0)
+print(well_test,np.shape(well_test))
+
+mnem = ['DEPTH', 'GR', 'CAL', 'RES', 'RHOB']
+unit = ['M', 'gAPI', 'in', 'ohm.m', 'g/cm3']
+
+project.well_data['test'] = {}
+
+project.well_data['test']['data'] = well_test
+project.well_data['test']['units'] = unit
+project.well_data['test']['mnemonics'] = mnem
+
+project.shape_check(mnemonics_replacement)
+
+# %%
+# split dataset by well
+
+tw_data,vw_data = preprocessing.well_train_test_split(['7-MP-22-BA','7-MP-50D-BA'],project.well_data)
+
+mega_data = preprocessing.data_assemble(tw_data,'data')
+print(np.shape(mega_data))
+
+# %%
+
+print(ref_mnemonics)
+
+def _remove_dummies(data):
+    data_1 = np.array(data).T
+    data_2 = data_1[~np.isnan(data_1).any(axis=1)]
+
+    return data_2
+
+mega_data = _remove_dummies(mega_data)
+
+print(np.shape(mega_data))
+
+y = mega_data[:,-1]
+X = np.delete(mega_data,(-1), axis=1)
+
+# %%
+
+lito_values = [{
+    "name": "ARENITO",
+    "short_name": "ARN",
+    "code": 49,
+    "patch_property": {
+        "color": "#ffff3f",
+        "hatch": ".",
+        "alpha": 1.0,
+        "hatchcolor": "#000000"
+    }
+    },
+    {
+    "name": "ARENITO ARGILOSO",
+    "short_name": "ARL",
+    "code": 25,
+    "patch_property": {
+        "color": "#7eff00",
+        "hatch": ".",
+        "alpha": 1.0,
+        "hatchcolor": "#000000"
+    }
+    }]
+
+for i in lito_values:
+    print(i["code"])
+
+print(project.class_counts(y,class_dict = lito_values))
+
+# %%
+
+machine_learning.settings(method = "GaussianNB", path='_ml_project')
+machine_learning.settings(method = "DecisionTreeClassifier", path='_ml_project')
+machine_learning.settings(method = "SVM", path='_ml_project')
+machine_learning.settings(method = "LogisticRegression", path='_ml_project')
+machine_learning.settings(method = "KNeighborsClassifier", path='_ml_project')
+machine_learning.settings(method = "RandomForestClassifier", path='_ml_project')
+machine_learning.settings(method = "XGBClassifier", path='_ml_project')
+machine_learning.settings(method = "CatBoostClassifier", path='_ml_project')
+
+# %%
+
+pre_pros = preprocessing.predict_processing(vw_data,'data')
+xy_raw = pre_pros.matrix_values()
+
+y_db = {}
+x_db = {}
+for well in xy_raw:
+    y_db[well] = xy_raw[well][:,-1]
+    x_db[well] = np.delete(xy_raw[well],(-1), axis=1)
+
+# %%
+for w in tw_data:
+    print(w)
+
+#machine_learning.fit(X,y,method = "GaussianNB", path = "_ml_project")
+#machine_learning.fit(X,y,method = "DecisionTreeClassifier", gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "DecisionTreeClassifier", path = "_ml_project")
+machine_learning.fit(X,y,method = "SVM", path = "_ml_project")
+#machine_learning.fit(X,y,method = "LogisticRegression", path = "_ml_project")
+#machine_learning.fit(X,y,method = "KNeighborsClassifier", gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "RandomForestClassifier", gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "XGBClassifier",gs = True, path = "_ml_project")
+
+#machine_learning.fit(X,y,method = "CatBoostClassifier",gs = True, path = "_ml_project")
+#machine_learning.fit(X,y,method = "CatBoostClassifier", path = "_ml_project")
+
+# %%
+
+class_db = {}
+
+for well in x_db:
+    class_db[well] = machine_learning.predict(x_db[well], method = "GaussianNB", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "DecisionTreeClassifier", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "SVM", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "LogisticRegression", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "KNeighborsClassifier", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "RandomForestClassifier", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "XGBClassifier", path = "_ml_project")
+    class_db[well] = machine_learning.predict(x_db[well], method = "CatBoostClassifier", path = "_ml_project")
+
+pre_pros.return_curve(class_db)
+
+# %%
+
+class_db = {}
+
+machine_learning.settings(method = "DecisionTreeClassifier")
+machine_learning.fit(X,y,method = "DecisionTreeClassifier")
+
+for well in x_db:
+    class_db[well] = machine_learning.predict(x_db[well], method = "DecisionTreeClassifier")
+
+# %%
+
+machine_learning.evaluation(class_db['7-MP-50D-BA'],y_db['7-MP-50D-BA'],decimals=5)
+
+# %%
+
+print(class_db['7-MP-50D-BA'])
+print(y_db['7-MP-50D-BA'])
+
+# %%
+print(list(set(y_db['7-MP-50D-BA'])))
+from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
+confusion_matrix(class_db['7-MP-50D-BA'], y_db['7-MP-50D-BA'], labels = np.array(list(set(y_db['7-MP-50D-BA']))))
+
+# %%
+print(classification_report(class_db['7-MP-50D-BA'], y_db['7-MP-50D-BA'] ,labels = np.array(list(set(y_db['7-MP-50D-BA'])))))
+# %%
diff --git a/stoneforge/tests/tests_ml/all_methods_test_replacement.py b/stoneforge/tests/tests_ml/all_methods_test_replacement.py
new file mode 100644
index 0000000..b040b28
--- /dev/null
+++ b/stoneforge/tests/tests_ml/all_methods_test_replacement.py
@@ -0,0 +1,236 @@
+# %%
+
+import numpy as np
+import sys
+import os
+import pandas
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+
+if __package__:
+    from ..data_replacement import *
+else:
+    print('passed lr')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import data_replacement
+
+if __package__:
+    from ..preprocessing import *
+else:
+    print('passed mgt')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import preprocessing
+
+# %%
+
+#project = preprocessing.project("D:\\appy_projetos\\wells")
+project = preprocessing.project("Y:\\appy_dados\\wells_es")
+project.import_folder()
+project.import_several_wells()
+
+print(project.well_names_paths)
+
+
+#%%
+
+mnemonics_replacement = {
+    'DEPTH':['DEPTH','MD'],
+    'GR':['GR'],
+    'CAL':['CAL','DCAL','HCAL','CALI'],
+    'RHOB':["RHOB","RHOZ","RHLA","RHBA","RHLA3","RHBA4"],
+    'RES':["ILD","LLD","HDRS","RT","AHT901","AT90","RT90"],
+    'NPHI':['NPHI','NPOR'],
+    'DT':['DT','DTCO']
+}
+
+ref_mnemonics = list(mnemonics_replacement.keys())
+
+project.data_replacement(mnemonics_replacement)
+project.convert_into_matrix(ref_mnemonics)
+
+# %%
+
+import matplotlib.pyplot as plt
+for i in project.well_data:
+    print(i)
+    fig, axes = plt.subplots(nrows=1, ncols=len(project.well_data[i]), figsize=(15, 5))
+    jj = 0
+    for j in project.well_data[i]:
+        print(j)
+        #x = project.well_data[i][j]['data']
+        #y = project.well_data[i][j]['data']
+        #axes[jj].plot(x, y, label='Curve 1')
+        axes[jj].set_title('Curve 1')
+        axes[jj].set_xlabel('x1')
+        axes[jj].set_ylabel('y')
+        axes[jj].legend()
+        jj += 1
+    break
+
+# %%
+
+tw_data,vw_data = preprocessing.well_train_test_split(['7-MP-22-BA','7-MP-50D-BA'],project.well_data)
+
+
+mega_data = preprocessing.data_assemble(tw_data,'data')
+print(np.shape(mega_data))
+
+
+# %%
+a = preprocessing.predict_processing(vw_data,'data')
+mega_data = a._remove_dummies(mega_data)
+print(np.shape(mega_data))
+
+# %%
+
+data_replacement.settings(method = "linear_regression_simple", path='_ml_project') # for the case there is polynomial 1D
+#data_replacement.settings(method = "linear_regression", path='_ml_project', degree = 2)
+#data_replacement.settings(method = "DecisionTreeClassifier", path='_ml_project')
+#data_replacement.settings(method = "SVM", path='_ml_project')
+#data_replacement.settings(method = "LogisticRegression", path='_ml_project')
+#data_replacement.settings(method = "KNeighborsClassifier", path='_ml_project')
+#data_replacement.settings(method = "RandomForestClassifier", path='_ml_project')
+#data_replacement.settings(method = "xgboost_regression", path='_ml_project')
+
+
+# %%
+
+mnemonics = []
+for i in mnemonics_replacement:
+    mnemonics.append(i)
+
+print(mnemonics)
+
+
+# %%
+
+y = mega_data[:,1] # 1 for RHOB 
+X = np.delete(mega_data,(1), axis=1) # 1 for RHOB also
+print(X)
+X = np.array(X, dtype='float') 
+y = np.array(y, dtype='float')
+print(y)
+
+# %%
+
+data_replacement.fit(X,y,method = "linear_regression_simple", path = "_ml_project")
+#data_replacement.fit(X,y,method = "decision_tree", gs = True, path = "_ml_project")
+#data_replacement.fit(X,y,method = "SVM", path = "_ml_project")
+#data_replacement.fit(X,y,method = "LogisticRegression", path = "_ml_project")
+#data_replacement.fit(X,y,method = "KNeighborsClassifier", path = "_ml_project")
+#data_replacement.fit(X,y,method = "RandomForestClassifier", path = "_ml_project")
+#data_replacement.fit(X,y,method = "xgboost_regression", path = '_ml_project')
+
+# %%
+import matplotlib.pyplot as plt
+pre_pros = preprocessing.predict_processing(vw_data,'data')
+xy_raw = pre_pros.matrix_values()
+
+y_db = {}
+x_db = {}
+for w in xy_raw:
+    #print( xy_raw[w])
+    y_db[w] = xy_raw[w][:,1]
+    x_db[w] = np.delete(xy_raw[w],(1), axis=1)
+    print(x_db)
+    ym_db = data_replacement.predict(x_db[w], method = "linear_regression_simple", path = "_ml_project")
+    plt.plot(ym_db, y_db[w],'.')
+    #plt.plot(ym_db,'.')
+    plt.grid()
+    plt.show()
+
+# %%
+
+class_db = {}
+
+for well in x_db:
+    class_db[well] = data_replacement.predict(x_db[well], method = "xgboost_regression", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "GaussianNB", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "DecisionTreeClassifier", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "SVM", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "LogisticRegression", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "KNeighborsClassifier", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "RandomForestClassifier", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "XGBClassifier", path = "_ml_project")
+    #class_db[well] = machine_learning.predict(x_db[well], method = "CatBoostClassifier", path = "_ml_project")
+
+pre_pros.return_curve(class_db)
+# %%
+
+#a = preprocessing.predict_processing(vw_data,'data')
+
+for w in vw_data:
+    x = np.delete(vw_data[w]['data'].T,(1), axis=1)
+    y = vw_data[w]['data'].T[:,1]
+    print(len(y))
+    is_nan_y = []
+    is_not_nan_x = []
+    for i in range(len(y)):
+        if np.isnan(y[i]):
+            is_nan_y.append(i)
+            #print(i)
+        if not np.isnan(x[i]).any():
+            is_not_nan_x.append(i)
+    is_nan_y = set(is_nan_y)
+    is_not_nan_x = set(is_not_nan_x)
+
+    l_data = vw_data[w]['data']
+    c_data = a._remove_dummies(l_data)
+
+    intersection = is_not_nan_x.intersection(is_nan_y)
+    print(list(intersection))
+
+    n_x_data = []
+    y_original = []
+    for i in intersection:
+        y_original.append(y[i])
+        n_x_data.append(x[i])
+    predictment = data_replacement.predict(n_x_data, method = "xgboost_regression", path = "_ml_project")
+    print("RHOB",len(predictment))
+    print(len(c_data[:,1]))
+    break
+
+# %%
+
+print(predictment)
+
+# %%
+x_r = a.matrix_values()
+
+y_vdb = {}
+x_db = {}
+for well in x_r:
+
+    print(np.shape(x_r[well]))
+    y_vdb[well] = x_r[well][:,0]
+    x_db[well] = np.delete(x_r[well],(0), axis=1)
+    print(x_db)
+    break
+
+
+# %%
+
+class_db = {}
+
+for x in x_db:
+    class_db[x] = data_replacement.predict(x_db[x], method = "GaussianNB", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "DecisionTreeClassifier", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "SVM", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "LogisticRegression", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "KNeighborsClassifier", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "RandomForestClassifier", path = "_ml_project")
+    class_db[x] = data_replacement.predict(x_db[x], method = "XGBClassifier", path = "_ml_project")
+
+a.return_curve(class_db)
+
+
+# %%
+
+data_replacement.settings(method = "GaussianNB")
+data_replacement.fit(X,y,method = "GaussianNB")
+
+for x in x_db:
+    class_db[x] = data_replacement.predict(x_db[x], method = "GaussianNB")
+    
+
+# %%
diff --git a/stoneforge/tests/tests_ml/catboost_fit_property.pkl b/stoneforge/tests/tests_ml/catboost_fit_property.pkl
new file mode 100644
index 0000000..08fa1bc
Binary files /dev/null and b/stoneforge/tests/tests_ml/catboost_fit_property.pkl differ
diff --git a/stoneforge/tests/tests_ml/catboost_info/catboost_training.json b/stoneforge/tests/tests_ml/catboost_info/catboost_training.json
new file mode 100644
index 0000000..5d219e3
--- /dev/null
+++ b/stoneforge/tests/tests_ml/catboost_info/catboost_training.json
@@ -0,0 +1,1004 @@
+{
+"meta":{"test_sets":[],"test_metrics":[],"learn_metrics":[{"best_value":"Min","name":"MultiClass"}],"launch_mode":"Train","parameters":"","iteration_count":1000,"learn_sets":["learn"],"name":"experiment"},
+"iterations":[
+{"learn":[1.160033152],"iteration":0,"passed_time":0.1625126759,"remaining_time":162.3501633},
+{"learn":[1.008673226],"iteration":1,"passed_time":0.1717322819,"remaining_time":85.69440868},
+{"learn":[0.8881235413],"iteration":2,"passed_time":0.1789713371,"remaining_time":59.47814102},
+{"learn":[0.7931164895],"iteration":3,"passed_time":0.1864556533,"remaining_time":46.42745767},
+{"learn":[0.7169791137],"iteration":4,"passed_time":0.194205187,"remaining_time":38.64683221},
+{"learn":[0.6550197311],"iteration":5,"passed_time":0.2025228716,"remaining_time":33.55128906},
+{"learn":[0.6018018746],"iteration":6,"passed_time":0.2099820934,"remaining_time":29.78745982},
+{"learn":[0.5567899648],"iteration":7,"passed_time":0.2169867823,"remaining_time":26.90636101},
+{"learn":[0.5153413669],"iteration":8,"passed_time":0.2246172778,"remaining_time":24.73285804},
+{"learn":[0.4798684623],"iteration":9,"passed_time":0.2318930543,"remaining_time":22.95741238},
+{"learn":[0.4483862615],"iteration":10,"passed_time":0.2389251553,"remaining_time":21.48154351},
+{"learn":[0.4200210977],"iteration":11,"passed_time":0.2462249772,"remaining_time":20.27252312},
+{"learn":[0.3952006938],"iteration":12,"passed_time":0.2533036315,"remaining_time":19.2315911},
+{"learn":[0.3731886431],"iteration":13,"passed_time":0.2603152973,"remaining_time":18.33363451},
+{"learn":[0.355255603],"iteration":14,"passed_time":0.2670341251,"remaining_time":17.53524088},
+{"learn":[0.3388989025],"iteration":15,"passed_time":0.2740204372,"remaining_time":16.85225689},
+{"learn":[0.3228762737],"iteration":16,"passed_time":0.2810524832,"remaining_time":16.25144653},
+{"learn":[0.3078431732],"iteration":17,"passed_time":0.2883555456,"remaining_time":15.73139699},
+{"learn":[0.2950196968],"iteration":18,"passed_time":0.2958786097,"remaining_time":15.2766798},
+{"learn":[0.2846853653],"iteration":19,"passed_time":0.3025060641,"remaining_time":14.82279714},
+{"learn":[0.2749589302],"iteration":20,"passed_time":0.3093333714,"remaining_time":14.42082717},
+{"learn":[0.2646729384],"iteration":21,"passed_time":0.3161128544,"remaining_time":14.05265325},
+{"learn":[0.2563332737],"iteration":22,"passed_time":0.3232045094,"remaining_time":13.72916546},
+{"learn":[0.2471175927],"iteration":23,"passed_time":0.3305582261,"remaining_time":13.4427012},
+{"learn":[0.2384867018],"iteration":24,"passed_time":0.3381425307,"remaining_time":13.1875587},
+{"learn":[0.2300573612],"iteration":25,"passed_time":0.3455175417,"remaining_time":12.94361868},
+{"learn":[0.2233724229],"iteration":26,"passed_time":0.3530433768,"remaining_time":12.72263724},
+{"learn":[0.2169478296],"iteration":27,"passed_time":0.3604787223,"remaining_time":12.51376136},
+{"learn":[0.2119406638],"iteration":28,"passed_time":0.3673378958,"remaining_time":12.2994861},
+{"learn":[0.2057649098],"iteration":29,"passed_time":0.3751763175,"remaining_time":12.13070093},
+{"learn":[0.2000520492],"iteration":30,"passed_time":0.3831156673,"remaining_time":11.97545425},
+{"learn":[0.1965126723],"iteration":31,"passed_time":0.3904184742,"remaining_time":11.81015885},
+{"learn":[0.1923360381],"iteration":32,"passed_time":0.397959356,"remaining_time":11.66141507},
+{"learn":[0.1892980359],"iteration":33,"passed_time":0.4048747002,"remaining_time":11.50320472},
+{"learn":[0.1850445532],"iteration":34,"passed_time":0.4120408635,"remaining_time":11.36055524},
+{"learn":[0.1812435958],"iteration":35,"passed_time":0.4186546631,"remaining_time":11.21064153},
+{"learn":[0.1779103494],"iteration":36,"passed_time":0.425546182,"remaining_time":11.07570198},
+{"learn":[0.1740249347],"iteration":37,"passed_time":0.4333262712,"remaining_time":10.96999665},
+{"learn":[0.1712776147],"iteration":38,"passed_time":0.4408587986,"remaining_time":10.86321296},
+{"learn":[0.1676729645],"iteration":39,"passed_time":0.4475877197,"remaining_time":10.74210527},
+{"learn":[0.1646288984],"iteration":40,"passed_time":0.4549047205,"remaining_time":10.64033236},
+{"learn":[0.1618642346],"iteration":41,"passed_time":0.4622819649,"remaining_time":10.54443149},
+{"learn":[0.1594769872],"iteration":42,"passed_time":0.4691202525,"remaining_time":10.44065306},
+{"learn":[0.1573902236],"iteration":43,"passed_time":0.4760471288,"remaining_time":10.3432058},
+{"learn":[0.15443359],"iteration":44,"passed_time":0.4831022765,"remaining_time":10.25250387},
+{"learn":[0.1526542844],"iteration":45,"passed_time":0.489840495,"remaining_time":10.15886592},
+{"learn":[0.1503569086],"iteration":46,"passed_time":0.4963354441,"remaining_time":10.06399315},
+{"learn":[0.1486240232],"iteration":47,"passed_time":0.5033738803,"remaining_time":9.983581959},
+{"learn":[0.1462510176],"iteration":48,"passed_time":0.5098444385,"remaining_time":9.895144103},
+{"learn":[0.1432071962],"iteration":49,"passed_time":0.5169515463,"remaining_time":9.82207938},
+{"learn":[0.1413126978],"iteration":50,"passed_time":0.5234910989,"remaining_time":9.741040252},
+{"learn":[0.1392605989],"iteration":51,"passed_time":0.5298613931,"remaining_time":9.659780781},
+{"learn":[0.1383447656],"iteration":52,"passed_time":0.5365066362,"remaining_time":9.586260084},
+{"learn":[0.1371648714],"iteration":53,"passed_time":0.5430422972,"remaining_time":9.51329654},
+{"learn":[0.1354617711],"iteration":54,"passed_time":0.54976788,"remaining_time":9.446011756},
+{"learn":[0.1340781432],"iteration":55,"passed_time":0.5568251611,"remaining_time":9.386481288},
+{"learn":[0.1333193027],"iteration":56,"passed_time":0.5631046499,"remaining_time":9.315924296},
+{"learn":[0.1314188429],"iteration":57,"passed_time":0.5701245751,"remaining_time":9.259609478},
+{"learn":[0.1300198007],"iteration":58,"passed_time":0.5770924924,"remaining_time":9.204136192},
+{"learn":[0.129290178],"iteration":59,"passed_time":0.583782979,"remaining_time":9.145933338},
+{"learn":[0.1281515222],"iteration":60,"passed_time":0.59046179,"remaining_time":9.089239685},
+{"learn":[0.1266043786],"iteration":61,"passed_time":0.5968918733,"remaining_time":9.030396405},
+{"learn":[0.1244648859],"iteration":62,"passed_time":0.6051644171,"remaining_time":9.000619982},
+{"learn":[0.1229691976],"iteration":63,"passed_time":0.6121211737,"remaining_time":8.952272165},
+{"learn":[0.1217672114],"iteration":64,"passed_time":0.618599703,"remaining_time":8.898318805},
+{"learn":[0.1210056657],"iteration":65,"passed_time":0.6246931606,"remaining_time":8.840354728},
+{"learn":[0.1200784689],"iteration":66,"passed_time":0.6316314309,"remaining_time":8.795703359},
+{"learn":[0.1195848609],"iteration":67,"passed_time":0.6378038951,"remaining_time":8.74166515},
+{"learn":[0.1184076767],"iteration":68,"passed_time":0.6445543522,"remaining_time":8.696813071},
+{"learn":[0.1173440878],"iteration":69,"passed_time":0.6517894708,"remaining_time":8.659488684},
+{"learn":[0.116348309],"iteration":70,"passed_time":0.6587836993,"remaining_time":8.619859953},
+{"learn":[0.1151051616],"iteration":71,"passed_time":0.6655825641,"remaining_time":8.578619716},
+{"learn":[0.1138342499],"iteration":72,"passed_time":0.6729213772,"remaining_time":8.545179681},
+{"learn":[0.1133271878],"iteration":73,"passed_time":0.6795095167,"remaining_time":8.503051519},
+{"learn":[0.1126772385],"iteration":74,"passed_time":0.6860846989,"remaining_time":8.461711286},
+{"learn":[0.1115231572],"iteration":75,"passed_time":0.6929289681,"remaining_time":8.424557454},
+{"learn":[0.1111092379],"iteration":76,"passed_time":0.6993729401,"remaining_time":8.383392515},
+{"learn":[0.1091238799],"iteration":77,"passed_time":0.7069298706,"remaining_time":8.356273599},
+{"learn":[0.1085269484],"iteration":78,"passed_time":0.7134023096,"remaining_time":8.317006672},
+{"learn":[0.1068956999],"iteration":79,"passed_time":0.721265393,"remaining_time":8.29455202},
+{"learn":[0.1060582577],"iteration":80,"passed_time":0.7281402206,"remaining_time":8.261245219},
+{"learn":[0.1058287447],"iteration":81,"passed_time":0.7351367944,"remaining_time":8.229946064},
+{"learn":[0.1052144507],"iteration":82,"passed_time":0.7422864078,"remaining_time":8.200923324},
+{"learn":[0.1043389529],"iteration":83,"passed_time":0.7493645054,"remaining_time":8.171641511},
+{"learn":[0.1039158369],"iteration":84,"passed_time":0.7562024988,"remaining_time":8.140297487},
+{"learn":[0.1036174631],"iteration":85,"passed_time":0.7628865517,"remaining_time":8.107887305},
+{"learn":[0.1030097397],"iteration":86,"passed_time":0.7701698768,"remaining_time":8.082357443},
+{"learn":[0.1026335959],"iteration":87,"passed_time":0.777520061,"remaining_time":8.057935178},
+{"learn":[0.1011456883],"iteration":88,"passed_time":0.7855846627,"remaining_time":8.0412093},
+{"learn":[0.1008214132],"iteration":89,"passed_time":0.7922079514,"remaining_time":8.01010262},
+{"learn":[0.1005665977],"iteration":90,"passed_time":0.7990336298,"remaining_time":7.981555708},
+{"learn":[0.09990963803],"iteration":91,"passed_time":0.8053738919,"remaining_time":7.94869015},
+{"learn":[0.09912540277],"iteration":92,"passed_time":0.8124313289,"remaining_time":7.923389412},
+{"learn":[0.09871654909],"iteration":93,"passed_time":0.819002844,"remaining_time":7.893793369},
+{"learn":[0.09854409629],"iteration":94,"passed_time":0.8253901055,"remaining_time":7.862926794},
+{"learn":[0.09794063951],"iteration":95,"passed_time":0.8324653005,"remaining_time":7.839048246},
+{"learn":[0.09762818943],"iteration":96,"passed_time":0.8392063735,"remaining_time":7.812405724},
+{"learn":[0.0961057723],"iteration":97,"passed_time":0.8467648387,"remaining_time":7.793692699},
+{"learn":[0.09456927472],"iteration":98,"passed_time":0.8541693399,"remaining_time":7.77380379},
+{"learn":[0.09386985699],"iteration":99,"passed_time":0.861042806,"remaining_time":7.749385254},
+{"learn":[0.09365653648],"iteration":100,"passed_time":0.8675335105,"remaining_time":7.721907188},
+{"learn":[0.09258156847],"iteration":101,"passed_time":0.8746821978,"remaining_time":7.700633467},
+{"learn":[0.09235329445],"iteration":102,"passed_time":0.8807253481,"remaining_time":7.670006187},
+{"learn":[0.0916293568],"iteration":103,"passed_time":0.8874580889,"remaining_time":7.645792765},
+{"learn":[0.0909260632],"iteration":104,"passed_time":0.8945035174,"remaining_time":7.6245776},
+{"learn":[0.09035906757],"iteration":105,"passed_time":0.9016999371,"remaining_time":7.604903243},
+{"learn":[0.08998253055],"iteration":106,"passed_time":0.9080410722,"remaining_time":7.578324088},
+{"learn":[0.08955201056],"iteration":107,"passed_time":0.9148732719,"remaining_time":7.556175542},
+{"learn":[0.08935522699],"iteration":108,"passed_time":0.9211726491,"remaining_time":7.529952572},
+{"learn":[0.08851084982],"iteration":109,"passed_time":0.9286772663,"remaining_time":7.513843336},
+{"learn":[0.08818847352],"iteration":110,"passed_time":0.9350570084,"remaining_time":7.488880004},
+{"learn":[0.08798163644],"iteration":111,"passed_time":0.9418164734,"remaining_time":7.467259182},
+{"learn":[0.08744401948],"iteration":112,"passed_time":0.9492692361,"remaining_time":7.451343472},
+{"learn":[0.08729597116],"iteration":113,"passed_time":0.955784085,"remaining_time":7.428286836},
+{"learn":[0.08668279496],"iteration":114,"passed_time":0.9629187258,"remaining_time":7.410287586},
+{"learn":[0.08650571258],"iteration":115,"passed_time":0.9697754931,"remaining_time":7.390358068},
+{"learn":[0.0859538422],"iteration":116,"passed_time":0.9770088517,"remaining_time":7.373494154},
+{"learn":[0.08465541738],"iteration":117,"passed_time":0.9844428383,"remaining_time":7.35829308},
+{"learn":[0.0843635614],"iteration":118,"passed_time":0.9907608571,"remaining_time":7.334960631},
+{"learn":[0.08426636623],"iteration":119,"passed_time":0.9980234834,"remaining_time":7.318838878},
+{"learn":[0.08389444031],"iteration":120,"passed_time":1.004400034,"remaining_time":7.296426695},
+{"learn":[0.08380993446],"iteration":121,"passed_time":1.010454176,"remaining_time":7.2719571},
+{"learn":[0.08368598789],"iteration":122,"passed_time":1.016648744,"remaining_time":7.248788198},
+{"learn":[0.08350338144],"iteration":123,"passed_time":1.022726673,"remaining_time":7.225069078},
+{"learn":[0.0834080719],"iteration":124,"passed_time":1.029749284,"remaining_time":7.208244988},
+{"learn":[0.08225333807],"iteration":125,"passed_time":1.037213626,"remaining_time":7.194640546},
+{"learn":[0.08211161066],"iteration":126,"passed_time":1.043368977,"remaining_time":7.17213478},
+{"learn":[0.08170022361],"iteration":127,"passed_time":1.050792121,"remaining_time":7.158521325},
+{"learn":[0.08087975074],"iteration":128,"passed_time":1.05810553,"remaining_time":7.144262921},
+{"learn":[0.08080126264],"iteration":129,"passed_time":1.065147894,"remaining_time":7.128297442},
+{"learn":[0.07986984362],"iteration":130,"passed_time":1.072786296,"remaining_time":7.116422069},
+{"learn":[0.0790369922],"iteration":131,"passed_time":1.080044187,"remaining_time":7.102108747},
+{"learn":[0.0786015375],"iteration":132,"passed_time":1.086229823,"remaining_time":7.080911702},
+{"learn":[0.07843459479],"iteration":133,"passed_time":1.092723752,"remaining_time":7.061931113},
+{"learn":[0.07796580983],"iteration":134,"passed_time":1.100193966,"remaining_time":7.049390969},
+{"learn":[0.07744102464],"iteration":135,"passed_time":1.107465474,"remaining_time":7.035663011},
+{"learn":[0.07737915284],"iteration":136,"passed_time":1.114667061,"remaining_time":7.021588856},
+{"learn":[0.07637387729],"iteration":137,"passed_time":1.122190654,"remaining_time":7.009625682},
+{"learn":[0.07594220937],"iteration":138,"passed_time":1.129418924,"remaining_time":6.995897076},
+{"learn":[0.07565616205],"iteration":139,"passed_time":1.136335329,"remaining_time":6.980345592},
+{"learn":[0.0754761529],"iteration":140,"passed_time":1.14311057,"remaining_time":6.964056596},
+{"learn":[0.0751585846],"iteration":141,"passed_time":1.149716229,"remaining_time":6.946876931},
+{"learn":[0.07501106424],"iteration":142,"passed_time":1.156373266,"remaining_time":6.930153071},
+{"learn":[0.07481101432],"iteration":143,"passed_time":1.163488715,"remaining_time":6.916294027},
+{"learn":[0.07472715816],"iteration":144,"passed_time":1.169244741,"remaining_time":6.894512096},
+{"learn":[0.07440649209],"iteration":145,"passed_time":1.175728808,"remaining_time":6.87720823},
+{"learn":[0.07426382699],"iteration":146,"passed_time":1.181813522,"remaining_time":6.857734249},
+{"learn":[0.074177802],"iteration":147,"passed_time":1.188100354,"remaining_time":6.83960474},
+{"learn":[0.07357188104],"iteration":148,"passed_time":1.1953337,"remaining_time":6.827040123},
+{"learn":[0.07267514898],"iteration":149,"passed_time":1.202425041,"remaining_time":6.813741901},
+{"learn":[0.07193176512],"iteration":150,"passed_time":1.210259144,"remaining_time":6.804702076},
+{"learn":[0.07179278459],"iteration":151,"passed_time":1.216327907,"remaining_time":6.785829376},
+{"learn":[0.07155002292],"iteration":152,"passed_time":1.223623651,"remaining_time":6.773916553},
+{"learn":[0.07147979815],"iteration":153,"passed_time":1.230156549,"remaining_time":6.757872989},
+{"learn":[0.07095310979],"iteration":154,"passed_time":1.237042832,"remaining_time":6.743878665},
+{"learn":[0.07051270925],"iteration":155,"passed_time":1.24407964,"remaining_time":6.730789845},
+{"learn":[0.07022730581],"iteration":156,"passed_time":1.251012411,"remaining_time":6.717219505},
+{"learn":[0.07005780821],"iteration":157,"passed_time":1.257862937,"remaining_time":6.703294894},
+{"learn":[0.06936379257],"iteration":158,"passed_time":1.264990639,"remaining_time":6.69092533},
+{"learn":[0.06892476281],"iteration":159,"passed_time":1.272656717,"remaining_time":6.681447763},
+{"learn":[0.0684406685],"iteration":160,"passed_time":1.28001019,"remaining_time":6.670363662},
+{"learn":[0.06836848449],"iteration":161,"passed_time":1.286367118,"remaining_time":6.654170645},
+{"learn":[0.06822367076],"iteration":162,"passed_time":1.29353016,"remaining_time":6.642237693},
+{"learn":[0.06816048776],"iteration":163,"passed_time":1.299717476,"remaining_time":6.625389085},
+{"learn":[0.06755148157],"iteration":164,"passed_time":1.306857449,"remaining_time":6.613490727},
+{"learn":[0.06718078867],"iteration":165,"passed_time":1.314289777,"remaining_time":6.60311852},
+{"learn":[0.06690541031],"iteration":166,"passed_time":1.32118343,"remaining_time":6.590094596},
+{"learn":[0.06664679935],"iteration":167,"passed_time":1.328788311,"remaining_time":6.580665923},
+{"learn":[0.06651157824],"iteration":168,"passed_time":1.335196917,"remaining_time":6.565376557},
+{"learn":[0.06635015477],"iteration":169,"passed_time":1.342156743,"remaining_time":6.552882921},
+{"learn":[0.06606164018],"iteration":170,"passed_time":1.349162414,"remaining_time":6.540676265},
+{"learn":[0.06595685035],"iteration":171,"passed_time":1.355809729,"remaining_time":6.526804973},
+{"learn":[0.06584660415],"iteration":172,"passed_time":1.362893878,"remaining_time":6.515105419},
+{"learn":[0.06534958652],"iteration":173,"passed_time":1.370067634,"remaining_time":6.503884284},
+{"learn":[0.06527935503],"iteration":174,"passed_time":1.376781833,"remaining_time":6.490542928},
+{"learn":[0.0650483267],"iteration":175,"passed_time":1.383495587,"remaining_time":6.477274792},
+{"learn":[0.06495804209],"iteration":176,"passed_time":1.390041845,"remaining_time":6.463301912},
+{"learn":[0.06490355729],"iteration":177,"passed_time":1.396352538,"remaining_time":6.448324642},
+{"learn":[0.06475577269],"iteration":178,"passed_time":1.403148415,"remaining_time":6.435669546},
+{"learn":[0.06413497121],"iteration":179,"passed_time":1.41024749,"remaining_time":6.424460787},
+{"learn":[0.06403771018],"iteration":180,"passed_time":1.417923413,"remaining_time":6.415907599},
+{"learn":[0.06364089812],"iteration":181,"passed_time":1.425288905,"remaining_time":6.405968816},
+{"learn":[0.06360417958],"iteration":182,"passed_time":1.432072309,"remaining_time":6.393459435},
+{"learn":[0.06355899668],"iteration":183,"passed_time":1.438263391,"remaining_time":6.378385472},
+{"learn":[0.06340817821],"iteration":184,"passed_time":1.444658621,"remaining_time":6.364306897},
+{"learn":[0.06278096686],"iteration":185,"passed_time":1.45165025,"remaining_time":6.352920985},
+{"learn":[0.06269710609],"iteration":186,"passed_time":1.458581596,"remaining_time":6.341319986},
+{"learn":[0.0626580215],"iteration":187,"passed_time":1.465182001,"remaining_time":6.328339281},
+{"learn":[0.06230129103],"iteration":188,"passed_time":1.472545555,"remaining_time":6.31870077},
+{"learn":[0.06222812109],"iteration":189,"passed_time":1.479234925,"remaining_time":6.306212047},
+{"learn":[0.06171282392],"iteration":190,"passed_time":1.486057607,"remaining_time":6.294348711},
+{"learn":[0.06121379032],"iteration":191,"passed_time":1.493321174,"remaining_time":6.284393273},
+{"learn":[0.06112618332],"iteration":192,"passed_time":1.499990311,"remaining_time":6.271980212},
+{"learn":[0.0610411749],"iteration":193,"passed_time":1.507224509,"remaining_time":6.261973992},
+{"learn":[0.06096070427],"iteration":194,"passed_time":1.514020693,"remaining_time":6.250187989},
+{"learn":[0.06085309209],"iteration":195,"passed_time":1.520959588,"remaining_time":6.239038311},
+{"learn":[0.06077136056],"iteration":196,"passed_time":1.527365457,"remaining_time":6.225758691},
+{"learn":[0.06074104592],"iteration":197,"passed_time":1.533269523,"remaining_time":6.210515948},
+{"learn":[0.06070054562],"iteration":198,"passed_time":1.54005998,"remaining_time":6.198934896},
+{"learn":[0.06045675478],"iteration":199,"passed_time":1.546424968,"remaining_time":6.185699873},
+{"learn":[0.06028869204],"iteration":200,"passed_time":1.552898302,"remaining_time":6.172963896},
+{"learn":[0.06012360119],"iteration":201,"passed_time":1.559855199,"remaining_time":6.162200241},
+{"learn":[0.0600874122],"iteration":202,"passed_time":1.566145124,"remaining_time":6.148855487},
+{"learn":[0.06005897814],"iteration":203,"passed_time":1.572773412,"remaining_time":6.136900177},
+{"learn":[0.0600217828],"iteration":204,"passed_time":1.578725818,"remaining_time":6.122375734},
+{"learn":[0.05997945438],"iteration":205,"passed_time":1.585392062,"remaining_time":6.110685907},
+{"learn":[0.05994691106],"iteration":206,"passed_time":1.591649877,"remaining_time":6.097479962},
+{"learn":[0.05960882317],"iteration":207,"passed_time":1.598659367,"remaining_time":6.087202976},
+{"learn":[0.05930281564],"iteration":208,"passed_time":1.606143256,"remaining_time":6.078752705},
+{"learn":[0.05912060249],"iteration":209,"passed_time":1.613100235,"remaining_time":6.068329457},
+{"learn":[0.05887919966],"iteration":210,"passed_time":1.620260987,"remaining_time":6.058701038},
+{"learn":[0.05859432326],"iteration":211,"passed_time":1.627190719,"remaining_time":6.048237203},
+{"learn":[0.05815093818],"iteration":212,"passed_time":1.634227617,"remaining_time":6.038202511},
+{"learn":[0.05811496324],"iteration":213,"passed_time":1.640508857,"remaining_time":6.025420382},
+{"learn":[0.05806162906],"iteration":214,"passed_time":1.647248117,"remaining_time":6.014371031},
+{"learn":[0.05755917018],"iteration":215,"passed_time":1.65469419,"remaining_time":6.00592706},
+{"learn":[0.05751995596],"iteration":216,"passed_time":1.6613112,"remaining_time":5.994500781},
+{"learn":[0.05721664162],"iteration":217,"passed_time":1.668596412,"remaining_time":5.985515568},
+{"learn":[0.05708141984],"iteration":218,"passed_time":1.675468738,"remaining_time":5.975073446},
+{"learn":[0.05694825463],"iteration":219,"passed_time":1.682120061,"remaining_time":5.963880218},
+{"learn":[0.0564540281],"iteration":220,"passed_time":1.689746311,"remaining_time":5.956164598},
+{"learn":[0.05626545471],"iteration":221,"passed_time":1.696951189,"remaining_time":5.946973085},
+{"learn":[0.0559537747],"iteration":222,"passed_time":1.704738337,"remaining_time":5.939828195},
+{"learn":[0.05591439256],"iteration":223,"passed_time":1.711079843,"remaining_time":5.927669454},
+{"learn":[0.0556218581],"iteration":224,"passed_time":1.717882587,"remaining_time":5.917151132},
+{"learn":[0.055201626],"iteration":225,"passed_time":1.725519807,"remaining_time":5.909523586},
+{"learn":[0.05497188306],"iteration":226,"passed_time":1.732231003,"remaining_time":5.89874258},
+{"learn":[0.05491863699],"iteration":227,"passed_time":1.738647548,"remaining_time":5.886999591},
+{"learn":[0.0546869132],"iteration":228,"passed_time":1.745360932,"remaining_time":5.876302528},
+{"learn":[0.05464517921],"iteration":229,"passed_time":1.752259089,"remaining_time":5.866258689},
+{"learn":[0.05460520691],"iteration":230,"passed_time":1.758444241,"remaining_time":5.85386849},
+{"learn":[0.0545601706],"iteration":231,"passed_time":1.764805591,"remaining_time":5.842115061},
+{"learn":[0.0542878517],"iteration":232,"passed_time":1.772539789,"remaining_time":5.834927118},
+{"learn":[0.05390079953],"iteration":233,"passed_time":1.780200056,"remaining_time":5.82749249},
+{"learn":[0.05387868233],"iteration":234,"passed_time":1.787118523,"remaining_time":5.817641149},
+{"learn":[0.05385980126],"iteration":235,"passed_time":1.793620567,"remaining_time":5.806466582},
+{"learn":[0.05383206925],"iteration":236,"passed_time":1.800829872,"remaining_time":5.797608405},
+{"learn":[0.05379781271],"iteration":237,"passed_time":1.807633566,"remaining_time":5.78746545},
+{"learn":[0.05364039204],"iteration":238,"passed_time":1.814206823,"remaining_time":5.776616706},
+{"learn":[0.05338457383],"iteration":239,"passed_time":1.821465295,"remaining_time":5.767973435},
+{"learn":[0.05334149483],"iteration":240,"passed_time":1.827513899,"remaining_time":5.755531326},
+{"learn":[0.05332399442],"iteration":241,"passed_time":1.834306473,"remaining_time":5.74547234},
+{"learn":[0.05327959471],"iteration":242,"passed_time":1.84070073,"remaining_time":5.734199393},
+{"learn":[0.05307932416],"iteration":243,"passed_time":1.847402198,"remaining_time":5.723918285},
+{"learn":[0.05289261602],"iteration":244,"passed_time":1.854515619,"remaining_time":5.714935886},
+{"learn":[0.05286431079],"iteration":245,"passed_time":1.860861355,"remaining_time":5.703615699},
+{"learn":[0.05267764482],"iteration":246,"passed_time":1.868347531,"remaining_time":5.695812514},
+{"learn":[0.05257629843],"iteration":247,"passed_time":1.875178372,"remaining_time":5.68602474},
+{"learn":[0.05232647038],"iteration":248,"passed_time":1.882737289,"remaining_time":5.678456644},
+{"learn":[0.05230154063],"iteration":249,"passed_time":1.889332225,"remaining_time":5.667996676},
+{"learn":[0.05225685233],"iteration":250,"passed_time":1.895674672,"remaining_time":5.65681406},
+{"learn":[0.05211971243],"iteration":251,"passed_time":1.902756937,"remaining_time":5.647865829},
+{"learn":[0.05209966226],"iteration":252,"passed_time":1.908955615,"remaining_time":5.636323496},
+{"learn":[0.05205208554],"iteration":253,"passed_time":1.915242495,"remaining_time":5.625082287},
+{"learn":[0.05197528718],"iteration":254,"passed_time":1.922413432,"remaining_time":5.616462772},
+{"learn":[0.05163197932],"iteration":255,"passed_time":1.929632441,"remaining_time":5.607994281},
+{"learn":[0.05160297843],"iteration":256,"passed_time":1.936760753,"remaining_time":5.599273305},
+{"learn":[0.05155568381],"iteration":257,"passed_time":1.943226111,"remaining_time":5.58865804},
+{"learn":[0.05149230371],"iteration":258,"passed_time":1.964093929,"remaining_time":5.619280314},
+{"learn":[0.0513888121],"iteration":259,"passed_time":1.970921286,"remaining_time":5.6095452},
+{"learn":[0.05136931083],"iteration":260,"passed_time":1.976899493,"remaining_time":5.597428066},
+{"learn":[0.0510104664],"iteration":261,"passed_time":1.984488178,"remaining_time":5.58989418},
+{"learn":[0.05099115208],"iteration":262,"passed_time":1.990577765,"remaining_time":5.578158984},
+{"learn":[0.05094886452],"iteration":263,"passed_time":1.99719391,"remaining_time":5.567934536},
+{"learn":[0.05091750418],"iteration":264,"passed_time":2.003636676,"remaining_time":5.55725644},
+{"learn":[0.05070296675],"iteration":265,"passed_time":2.010083785,"remaining_time":5.546622174},
+{"learn":[0.05067001411],"iteration":266,"passed_time":2.016931741,"remaining_time":5.537119723},
+{"learn":[0.05058679132],"iteration":267,"passed_time":2.02313244,"remaining_time":5.525869202},
+{"learn":[0.05056392918],"iteration":268,"passed_time":2.030058019,"remaining_time":5.516626067},
+{"learn":[0.05054119534],"iteration":269,"passed_time":2.036638425,"remaining_time":5.506466852},
+{"learn":[0.05024795987],"iteration":270,"passed_time":2.043751511,"remaining_time":5.497766979},
+{"learn":[0.05023367555],"iteration":271,"passed_time":2.051131411,"remaining_time":5.489792895},
+{"learn":[0.04985783531],"iteration":272,"passed_time":2.058335616,"remaining_time":5.481355284},
+{"learn":[0.04983536449],"iteration":273,"passed_time":2.064787644,"remaining_time":5.470933685},
+{"learn":[0.04959688184],"iteration":274,"passed_time":2.07216512,"remaining_time":5.462980772},
+{"learn":[0.04942496289],"iteration":275,"passed_time":2.079126692,"remaining_time":5.453941032},
+{"learn":[0.04940252204],"iteration":276,"passed_time":2.085697516,"remaining_time":5.443896404},
+{"learn":[0.04910836123],"iteration":277,"passed_time":2.093004185,"remaining_time":5.435787847},
+{"learn":[0.0489273979],"iteration":278,"passed_time":2.100870784,"remaining_time":5.429132026},
+{"learn":[0.04855702539],"iteration":279,"passed_time":2.108145839,"remaining_time":5.420946442},
+{"learn":[0.04846045331],"iteration":280,"passed_time":2.115556433,"remaining_time":5.413114146},
+{"learn":[0.04842280525],"iteration":281,"passed_time":2.122079497,"remaining_time":5.403025101},
+{"learn":[0.04832033878],"iteration":282,"passed_time":2.129595821,"remaining_time":5.395477752},
+{"learn":[0.04829444022],"iteration":283,"passed_time":2.135642428,"remaining_time":5.384225276},
+{"learn":[0.04826563825],"iteration":284,"passed_time":2.141763221,"remaining_time":5.373195449},
+{"learn":[0.04797336458],"iteration":285,"passed_time":2.149420998,"remaining_time":5.366037038},
+{"learn":[0.04776590546],"iteration":286,"passed_time":2.156861158,"remaining_time":5.358334516},
+{"learn":[0.04750622704],"iteration":287,"passed_time":2.164420726,"remaining_time":5.350929018},
+{"learn":[0.04740055322],"iteration":288,"passed_time":2.171281411,"remaining_time":5.341803057},
+{"learn":[0.04735226902],"iteration":289,"passed_time":2.178083699,"remaining_time":5.332549747},
+{"learn":[0.04714561977],"iteration":290,"passed_time":2.185530993,"remaining_time":5.324884791},
+{"learn":[0.04712487644],"iteration":291,"passed_time":2.192341351,"remaining_time":5.315676973},
+{"learn":[0.04709006259],"iteration":292,"passed_time":2.19913752,"remaining_time":5.306451284},
+{"learn":[0.04699735783],"iteration":293,"passed_time":2.205476786,"remaining_time":5.296144934},
+{"learn":[0.04697710322],"iteration":294,"passed_time":2.212420882,"remaining_time":5.287310921},
+{"learn":[0.04684743755],"iteration":295,"passed_time":2.219331658,"remaining_time":5.27841043},
+{"learn":[0.0468095009],"iteration":296,"passed_time":2.225700829,"remaining_time":5.268241357},
+{"learn":[0.04679805734],"iteration":297,"passed_time":2.232178614,"remaining_time":5.258353649},
+{"learn":[0.04677093189],"iteration":298,"passed_time":2.238312449,"remaining_time":5.247682364},
+{"learn":[0.04670214526],"iteration":299,"passed_time":2.24537351,"remaining_time":5.239204857},
+{"learn":[0.04669014568],"iteration":300,"passed_time":2.25146278,"remaining_time":5.228480011},
+{"learn":[0.04660665683],"iteration":301,"passed_time":2.25786554,"remaining_time":5.218510421},
+{"learn":[0.04659342111],"iteration":302,"passed_time":2.264943932,"remaining_time":5.210118549},
+{"learn":[0.04654444481],"iteration":303,"passed_time":2.271934091,"remaining_time":5.201533313},
+{"learn":[0.04652279356],"iteration":304,"passed_time":2.278984028,"remaining_time":5.193094752},
+{"learn":[0.0462779216],"iteration":305,"passed_time":2.286480901,"remaining_time":5.185678906},
+{"learn":[0.04618517719],"iteration":306,"passed_time":2.294081851,"remaining_time":5.178497468},
+{"learn":[0.04617104011],"iteration":307,"passed_time":2.300886997,"remaining_time":5.169525331},
+{"learn":[0.04613505786],"iteration":308,"passed_time":2.307687262,"remaining_time":5.160556304},
+{"learn":[0.04603009761],"iteration":309,"passed_time":2.314791442,"remaining_time":5.152277726},
+{"learn":[0.045925653],"iteration":310,"passed_time":2.321546959,"remaining_time":5.143234259},
+{"learn":[0.04590150654],"iteration":311,"passed_time":2.328034687,"remaining_time":5.133614951},
+{"learn":[0.04588582067],"iteration":312,"passed_time":2.334330674,"remaining_time":5.123594801},
+{"learn":[0.04582769457],"iteration":313,"passed_time":2.340694737,"remaining_time":5.113747101},
+{"learn":[0.04581691864],"iteration":314,"passed_time":2.346683554,"remaining_time":5.103105506},
+{"learn":[0.04549492839],"iteration":315,"passed_time":2.353628237,"remaining_time":5.094562386},
+{"learn":[0.04519770776],"iteration":316,"passed_time":2.361267441,"remaining_time":5.087525749},
+{"learn":[0.0451400209],"iteration":317,"passed_time":2.368136444,"remaining_time":5.078833506},
+{"learn":[0.04505667641],"iteration":318,"passed_time":2.375404504,"remaining_time":5.0710046},
+{"learn":[0.0450057904],"iteration":319,"passed_time":2.382198479,"remaining_time":5.062171769},
+{"learn":[0.0449427691],"iteration":320,"passed_time":2.388873209,"remaining_time":5.053099404},
+{"learn":[0.04486577277],"iteration":321,"passed_time":2.396002277,"remaining_time":5.044998583},
+{"learn":[0.04457760413],"iteration":322,"passed_time":2.40328503,"remaining_time":5.037225899},
+{"learn":[0.04450235461],"iteration":323,"passed_time":2.410713385,"remaining_time":5.029760026},
+{"learn":[0.04425032736],"iteration":324,"passed_time":2.417800013,"remaining_time":5.021584642},
+{"learn":[0.04404845427],"iteration":325,"passed_time":2.425082213,"remaining_time":5.013820281},
+{"learn":[0.04403499328],"iteration":326,"passed_time":2.432356055,"remaining_time":5.006041667},
+{"learn":[0.04399852055],"iteration":327,"passed_time":2.438329094,"remaining_time":4.99560107},
+{"learn":[0.04395914338],"iteration":328,"passed_time":2.445112135,"remaining_time":4.986839643},
+{"learn":[0.04381322626],"iteration":329,"passed_time":2.4517407,"remaining_time":4.977776572},
+{"learn":[0.04369537893],"iteration":330,"passed_time":2.45841187,"remaining_time":4.968814323},
+{"learn":[0.04368498071],"iteration":331,"passed_time":2.464651508,"remaining_time":4.958997612},
+{"learn":[0.04366617149],"iteration":332,"passed_time":2.471202241,"remaining_time":4.949825509},
+{"learn":[0.04365319924],"iteration":333,"passed_time":2.477722963,"remaining_time":4.940609262},
+{"learn":[0.04362900955],"iteration":334,"passed_time":2.484616881,"remaining_time":4.932149927},
+{"learn":[0.04361270042],"iteration":335,"passed_time":2.491837711,"remaining_time":4.924345952},
+{"learn":[0.04360066891],"iteration":336,"passed_time":2.498989164,"remaining_time":4.916408948},
+{"learn":[0.04341491548],"iteration":337,"passed_time":2.506646521,"remaining_time":4.909467447},
+{"learn":[0.04340320547],"iteration":338,"passed_time":2.513398132,"remaining_time":4.90075565},
+{"learn":[0.04339460433],"iteration":339,"passed_time":2.519540355,"remaining_time":4.890872453},
+{"learn":[0.04336997843],"iteration":340,"passed_time":2.526107255,"remaining_time":4.88183191},
+{"learn":[0.04329545696],"iteration":341,"passed_time":2.533013153,"remaining_time":4.873458055},
+{"learn":[0.04326067858],"iteration":342,"passed_time":2.539774045,"remaining_time":4.864815007},
+{"learn":[0.043251725],"iteration":343,"passed_time":2.546358384,"remaining_time":4.85584622},
+{"learn":[0.04310192278],"iteration":344,"passed_time":2.552636574,"remaining_time":4.846310017},
+{"learn":[0.04302347742],"iteration":345,"passed_time":2.559564258,"remaining_time":4.838020303},
+{"learn":[0.04290261525],"iteration":346,"passed_time":2.566225282,"remaining_time":4.829236626},
+{"learn":[0.04279411047],"iteration":347,"passed_time":2.573102775,"remaining_time":4.820870716},
+{"learn":[0.0427689654],"iteration":348,"passed_time":2.579702985,"remaining_time":4.811996113},
+{"learn":[0.04275516652],"iteration":349,"passed_time":2.585357982,"remaining_time":4.801379109},
+{"learn":[0.0427383065],"iteration":350,"passed_time":2.592718263,"remaining_time":4.793943455},
+{"learn":[0.04264768964],"iteration":351,"passed_time":2.599679367,"remaining_time":4.785773381},
+{"learn":[0.04263274798],"iteration":352,"passed_time":2.606266766,"remaining_time":4.776925205},
+{"learn":[0.04261823376],"iteration":353,"passed_time":2.612423286,"remaining_time":4.767303511},
+{"learn":[0.04235116715],"iteration":354,"passed_time":2.62008826,"remaining_time":4.760442051},
+{"learn":[0.0423248028],"iteration":355,"passed_time":2.627901029,"remaining_time":4.753843435},
+{"learn":[0.04224058018],"iteration":356,"passed_time":2.635143532,"remaining_time":4.7462109},
+{"learn":[0.04220636345],"iteration":357,"passed_time":2.642190583,"remaining_time":4.73823004},
+{"learn":[0.0421009732],"iteration":358,"passed_time":2.649204657,"remaining_time":4.730195501},
+{"learn":[0.0418636344],"iteration":359,"passed_time":2.656963758,"remaining_time":4.723491125},
+{"learn":[0.04184384326],"iteration":360,"passed_time":2.664633501,"remaining_time":4.716622734},
+{"learn":[0.04179635822],"iteration":361,"passed_time":2.671375057,"remaining_time":4.708114051},
+{"learn":[0.0417605827],"iteration":362,"passed_time":2.678229163,"remaining_time":4.699812608},
+{"learn":[0.04158459246],"iteration":363,"passed_time":2.685479566,"remaining_time":4.69221155},
+{"learn":[0.04152619311],"iteration":364,"passed_time":2.692386671,"remaining_time":4.684015167},
+{"learn":[0.04149521981],"iteration":365,"passed_time":2.699284403,"remaining_time":4.675809594},
+{"learn":[0.0414700846],"iteration":366,"passed_time":2.706231028,"remaining_time":4.667695479},
+{"learn":[0.04143564518],"iteration":367,"passed_time":2.713081627,"remaining_time":4.659422793},
+{"learn":[0.04142648302],"iteration":368,"passed_time":2.719379239,"remaining_time":4.650212194},
+{"learn":[0.04141572671],"iteration":369,"passed_time":2.726702973,"remaining_time":4.642764522},
+{"learn":[0.04123739104],"iteration":370,"passed_time":2.733974199,"remaining_time":4.635228493},
+{"learn":[0.04122441316],"iteration":371,"passed_time":2.740810881,"remaining_time":4.626960305},
+{"learn":[0.04100765097],"iteration":372,"passed_time":2.748325362,"remaining_time":4.619839148},
+{"learn":[0.04092182214],"iteration":373,"passed_time":2.755291821,"remaining_time":4.61179861},
+{"learn":[0.04091235533],"iteration":374,"passed_time":2.761986762,"remaining_time":4.60331127},
+{"learn":[0.04088646718],"iteration":375,"passed_time":2.767906837,"remaining_time":4.593547517},
+{"learn":[0.04086748565],"iteration":376,"passed_time":2.774430087,"remaining_time":4.584800914},
+{"learn":[0.04074819336],"iteration":377,"passed_time":2.781719151,"remaining_time":4.577326222},
+{"learn":[0.04073436745],"iteration":378,"passed_time":2.788453911,"remaining_time":4.56894427},
+{"learn":[0.04067744945],"iteration":379,"passed_time":2.796480094,"remaining_time":4.562678048},
+{"learn":[0.04055765473],"iteration":380,"passed_time":2.804106321,"remaining_time":4.555752789},
+{"learn":[0.04044099743],"iteration":381,"passed_time":2.810696192,"remaining_time":4.547147243},
+{"learn":[0.04035737197],"iteration":382,"passed_time":2.817403399,"remaining_time":4.538741246},
+{"learn":[0.04031457422],"iteration":383,"passed_time":2.824200292,"remaining_time":4.530487969},
+{"learn":[0.04028701475],"iteration":384,"passed_time":2.830069212,"remaining_time":4.52075991},
+{"learn":[0.04027829299],"iteration":385,"passed_time":2.836191539,"remaining_time":4.511454936},
+{"learn":[0.04025611345],"iteration":386,"passed_time":2.843669099,"remaining_time":4.504313069},
+{"learn":[0.04020513905],"iteration":387,"passed_time":2.850008567,"remaining_time":4.495374337},
+{"learn":[0.04018833309],"iteration":388,"passed_time":2.856621365,"remaining_time":4.486878288},
+{"learn":[0.04017483009],"iteration":389,"passed_time":2.863121199,"remaining_time":4.478215208},
+{"learn":[0.04012913099],"iteration":390,"passed_time":2.869736215,"remaining_time":4.469742595},
+{"learn":[0.03990729664],"iteration":391,"passed_time":2.877173909,"remaining_time":4.46255545},
+{"learn":[0.03986318057],"iteration":392,"passed_time":2.883775544,"remaining_time":4.454075712},
+{"learn":[0.03979806117],"iteration":393,"passed_time":2.891182926,"remaining_time":4.446844804},
+{"learn":[0.03978209855],"iteration":394,"passed_time":2.897276072,"remaining_time":4.43760006},
+{"learn":[0.0395206444],"iteration":395,"passed_time":2.904930659,"remaining_time":4.430752823},
+{"learn":[0.03939167005],"iteration":396,"passed_time":2.912510648,"remaining_time":4.423788213},
+{"learn":[0.03936557393],"iteration":397,"passed_time":2.919956111,"remaining_time":4.416617033},
+{"learn":[0.03931827208],"iteration":398,"passed_time":2.927474675,"remaining_time":4.409554585},
+{"learn":[0.03913576714],"iteration":399,"passed_time":2.934649537,"remaining_time":4.401974305},
+{"learn":[0.03911795541],"iteration":400,"passed_time":2.941138639,"remaining_time":4.393371682},
+{"learn":[0.03908934809],"iteration":401,"passed_time":2.94733984,"remaining_time":4.384351304},
+{"learn":[0.03904693822],"iteration":402,"passed_time":2.954243774,"remaining_time":4.376385939},
+{"learn":[0.03902893089],"iteration":403,"passed_time":2.960714227,"remaining_time":4.367786334},
+{"learn":[0.03901413031],"iteration":404,"passed_time":2.966927736,"remaining_time":4.35881976},
+{"learn":[0.03882856931],"iteration":405,"passed_time":2.974380127,"remaining_time":4.3516793},
+{"learn":[0.03872483743],"iteration":406,"passed_time":2.981181599,"remaining_time":4.343588914},
+{"learn":[0.03863167684],"iteration":407,"passed_time":2.988716066,"remaining_time":4.336568409},
+{"learn":[0.0386171227],"iteration":408,"passed_time":2.994586046,"remaining_time":4.327140227},
+{"learn":[0.03853694945],"iteration":409,"passed_time":3.001483086,"remaining_time":4.319207367},
+{"learn":[0.03843725339],"iteration":410,"passed_time":3.008660221,"remaining_time":4.31168095},
+{"learn":[0.03838455136],"iteration":411,"passed_time":3.015922427,"remaining_time":4.304277638},
+{"learn":[0.0381644459],"iteration":412,"passed_time":3.023423846,"remaining_time":4.297215006},
+{"learn":[0.03801408053],"iteration":413,"passed_time":3.030544616,"remaining_time":4.289611461},
+{"learn":[0.03798923372],"iteration":414,"passed_time":3.037198611,"remaining_time":4.281352259},
+{"learn":[0.03790103928],"iteration":415,"passed_time":3.044204657,"remaining_time":4.273594999},
+{"learn":[0.03786993306],"iteration":416,"passed_time":3.051389134,"remaining_time":4.266090804},
+{"learn":[0.03782021637],"iteration":417,"passed_time":3.057895085,"remaining_time":4.257643396},
+{"learn":[0.03766285397],"iteration":418,"passed_time":3.065372959,"remaining_time":4.250552957},
+{"learn":[0.03755764554],"iteration":419,"passed_time":3.077837551,"remaining_time":4.250347094},
+{"learn":[0.03754274721],"iteration":420,"passed_time":3.085141456,"remaining_time":4.242985518},
+{"learn":[0.03734306282],"iteration":421,"passed_time":3.092480535,"remaining_time":4.235672391},
+{"learn":[0.03728477824],"iteration":422,"passed_time":3.099230279,"remaining_time":4.227555251},
+{"learn":[0.03721575043],"iteration":423,"passed_time":3.105767184,"remaining_time":4.21915542},
+{"learn":[0.03714255782],"iteration":424,"passed_time":3.112811574,"remaining_time":4.211450954},
+{"learn":[0.03713252364],"iteration":425,"passed_time":3.119962202,"remaining_time":4.203892733},
+{"learn":[0.03710962457],"iteration":426,"passed_time":3.126764055,"remaining_time":4.195868392},
+{"learn":[0.03708823304],"iteration":427,"passed_time":3.133517644,"remaining_time":4.187785263},
+{"learn":[0.03702499593],"iteration":428,"passed_time":3.140666808,"remaining_time":4.180234842},
+{"learn":[0.03698715631],"iteration":429,"passed_time":3.147732523,"remaining_time":4.17257567},
+{"learn":[0.03690941265],"iteration":430,"passed_time":3.154783989,"remaining_time":4.16490044},
+{"learn":[0.0368940519],"iteration":431,"passed_time":3.161687301,"remaining_time":4.157033303},
+{"learn":[0.0368827281],"iteration":432,"passed_time":3.168514107,"remaining_time":4.149070436},
+{"learn":[0.03686017589],"iteration":433,"passed_time":3.174679174,"remaining_time":4.140249798},
+{"learn":[0.03683215817],"iteration":434,"passed_time":3.181836863,"remaining_time":4.132730639},
+{"learn":[0.03681344065],"iteration":435,"passed_time":3.188852609,"remaining_time":4.125029522},
+{"learn":[0.03677739241],"iteration":436,"passed_time":3.195371815,"remaining_time":4.116691834},
+{"learn":[0.03672050285],"iteration":437,"passed_time":3.20230081,"remaining_time":4.108888254},
+{"learn":[0.03668995921],"iteration":438,"passed_time":3.208783137,"remaining_time":4.100517858},
+{"learn":[0.03668093144],"iteration":439,"passed_time":3.215767563,"remaining_time":4.092795081},
+{"learn":[0.03666033061],"iteration":440,"passed_time":3.22213959,"remaining_time":4.084299389},
+{"learn":[0.03664108247],"iteration":441,"passed_time":3.228659879,"remaining_time":4.07600048},
+{"learn":[0.03663428851],"iteration":442,"passed_time":3.235512794,"remaining_time":4.068127825},
+{"learn":[0.03660461632],"iteration":443,"passed_time":3.242119129,"remaining_time":4.059950981},
+{"learn":[0.03651605123],"iteration":444,"passed_time":3.249503133,"remaining_time":4.052751098},
+{"learn":[0.03649295577],"iteration":445,"passed_time":3.256933502,"remaining_time":4.045607982},
+{"learn":[0.03647505553],"iteration":446,"passed_time":3.263657368,"remaining_time":4.037589541},
+{"learn":[0.036463431],"iteration":447,"passed_time":3.270091516,"remaining_time":4.029219904},
+{"learn":[0.03642268876],"iteration":448,"passed_time":3.276889392,"remaining_time":4.021305245},
+{"learn":[0.03630821851],"iteration":449,"passed_time":3.284099994,"remaining_time":4.013899993},
+{"learn":[0.03630113441],"iteration":450,"passed_time":3.290972749,"remaining_time":4.006084344},
+{"learn":[0.03622212121],"iteration":451,"passed_time":3.298578181,"remaining_time":3.999161158},
+{"learn":[0.03610920182],"iteration":452,"passed_time":3.30542277,"remaining_time":3.991316237},
+{"learn":[0.03609758381],"iteration":453,"passed_time":3.312917693,"remaining_time":3.984257842},
+{"learn":[0.03606740268],"iteration":454,"passed_time":3.319403095,"remaining_time":3.975988323},
+{"learn":[0.03599516587],"iteration":455,"passed_time":3.326724417,"remaining_time":3.968723866},
+{"learn":[0.03582319582],"iteration":456,"passed_time":3.334197854,"remaining_time":3.9616399},
+{"learn":[0.0358146809],"iteration":457,"passed_time":3.340780165,"remaining_time":3.953499672},
+{"learn":[0.03578706065],"iteration":458,"passed_time":3.347638436,"remaining_time":3.94569149},
+{"learn":[0.03575268608],"iteration":459,"passed_time":3.354599487,"remaining_time":3.938008094},
+{"learn":[0.03574386428],"iteration":460,"passed_time":3.361302078,"remaining_time":3.93002564},
+{"learn":[0.03569364704],"iteration":461,"passed_time":3.367891563,"remaining_time":3.921917015},
+{"learn":[0.03568063436],"iteration":462,"passed_time":3.374720479,"remaining_time":3.914092651},
+{"learn":[0.0356598993],"iteration":463,"passed_time":3.381521012,"remaining_time":3.90623979},
+{"learn":[0.03564854951],"iteration":464,"passed_time":3.388319663,"remaining_time":3.89838929},
+{"learn":[0.03551634925],"iteration":465,"passed_time":3.39600505,"remaining_time":3.891559435},
+{"learn":[0.03549420393],"iteration":466,"passed_time":3.403406429,"remaining_time":3.88440177},
+{"learn":[0.03547956297],"iteration":467,"passed_time":3.410839524,"remaining_time":3.877279117},
+{"learn":[0.03544556623],"iteration":468,"passed_time":3.417807174,"remaining_time":3.869628165},
+{"learn":[0.03543406687],"iteration":469,"passed_time":3.424099938,"remaining_time":3.861219079},
+{"learn":[0.0353842035],"iteration":470,"passed_time":3.430675985,"remaining_time":3.853137146},
+{"learn":[0.03531320695],"iteration":471,"passed_time":3.437618554,"remaining_time":3.845471603},
+{"learn":[0.03530502567],"iteration":472,"passed_time":3.443874281,"remaining_time":3.837043861},
+{"learn":[0.03527230915],"iteration":473,"passed_time":3.450863413,"remaining_time":3.829439147},
+{"learn":[0.0352264688],"iteration":474,"passed_time":3.457736196,"remaining_time":3.821708427},
+{"learn":[0.03520414522],"iteration":475,"passed_time":3.465103091,"remaining_time":3.814525252},
+{"learn":[0.03509263104],"iteration":476,"passed_time":3.471980631,"remaining_time":3.806804759},
+{"learn":[0.03508414695],"iteration":477,"passed_time":3.479206346,"remaining_time":3.799468018},
+{"learn":[0.03507026336],"iteration":478,"passed_time":3.485583124,"remaining_time":3.791208367},
+{"learn":[0.03491132216],"iteration":479,"passed_time":3.492601334,"remaining_time":3.783651445},
+{"learn":[0.03490467698],"iteration":480,"passed_time":3.499091631,"remaining_time":3.775527145},
+{"learn":[0.03487591791],"iteration":481,"passed_time":3.505043388,"remaining_time":3.766830861},
+{"learn":[0.03485937578],"iteration":482,"passed_time":3.511497185,"remaining_time":3.758683322},
+{"learn":[0.0348484559],"iteration":483,"passed_time":3.518585751,"remaining_time":3.75121952},
+{"learn":[0.03472358165],"iteration":484,"passed_time":3.52562132,"remaining_time":3.743700989},
+{"learn":[0.03460984075],"iteration":485,"passed_time":3.532876872,"remaining_time":3.736417103},
+{"learn":[0.0345972085],"iteration":486,"passed_time":3.539286239,"remaining_time":3.728241972},
+{"learn":[0.03457688509],"iteration":487,"passed_time":3.546045457,"remaining_time":3.720441136},
+{"learn":[0.03450145145],"iteration":488,"passed_time":3.552587459,"remaining_time":3.71241757},
+{"learn":[0.03444675883],"iteration":489,"passed_time":3.560039717,"remaining_time":3.705347461},
+{"learn":[0.03438159948],"iteration":490,"passed_time":3.567386239,"remaining_time":3.698166183},
+{"learn":[0.03435074164],"iteration":491,"passed_time":3.574509943,"remaining_time":3.690754169},
+{"learn":[0.03431876669],"iteration":492,"passed_time":3.582068096,"remaining_time":3.683790111},
+{"learn":[0.03429137404],"iteration":493,"passed_time":3.588965441,"remaining_time":3.676146788},
+{"learn":[0.03427214258],"iteration":494,"passed_time":3.595921721,"remaining_time":3.668566604},
+{"learn":[0.03423312763],"iteration":495,"passed_time":3.602905475,"remaining_time":3.661016853},
+{"learn":[0.03421503366],"iteration":496,"passed_time":3.609926516,"remaining_time":3.653507118},
+{"learn":[0.03420128703],"iteration":497,"passed_time":3.617030933,"remaining_time":3.646083391},
+{"learn":[0.03406542147],"iteration":498,"passed_time":3.624424774,"remaining_time":3.638951526},
+{"learn":[0.03390318958],"iteration":499,"passed_time":3.631552953,"remaining_time":3.631552953},
+{"learn":[0.03389378103],"iteration":500,"passed_time":3.638514289,"remaining_time":3.623989282},
+{"learn":[0.03387579278],"iteration":501,"passed_time":3.645369056,"remaining_time":3.616322291},
+{"learn":[0.03379886281],"iteration":502,"passed_time":3.651817313,"remaining_time":3.608256868},
+{"learn":[0.0337743283],"iteration":503,"passed_time":3.658369158,"remaining_time":3.600299807},
+{"learn":[0.03376697859],"iteration":504,"passed_time":3.665109757,"remaining_time":3.592533326},
+{"learn":[0.03375738076],"iteration":505,"passed_time":3.672416579,"remaining_time":3.585323696},
+{"learn":[0.03372691183],"iteration":506,"passed_time":3.679458735,"remaining_time":3.577856324},
+{"learn":[0.03370408455],"iteration":507,"passed_time":3.685862464,"remaining_time":3.569772308},
+{"learn":[0.03359087209],"iteration":508,"passed_time":3.69303899,"remaining_time":3.562440362},
+{"learn":[0.03355356579],"iteration":509,"passed_time":3.700071019,"remaining_time":3.554970195},
+{"learn":[0.03348260778],"iteration":510,"passed_time":3.70764842,"remaining_time":3.548023635},
+{"learn":[0.03338689268],"iteration":511,"passed_time":3.714810982,"remaining_time":3.540679217},
+{"learn":[0.03337436405],"iteration":512,"passed_time":3.721554631,"remaining_time":3.532937827},
+{"learn":[0.0333263933],"iteration":513,"passed_time":3.729213512,"remaining_time":3.526065694},
+{"learn":[0.03330845823],"iteration":514,"passed_time":3.736105526,"remaining_time":3.51846831},
+{"learn":[0.03329755619],"iteration":515,"passed_time":3.742947656,"remaining_time":3.510826871},
+{"learn":[0.03329034672],"iteration":516,"passed_time":3.749491823,"remaining_time":3.502910156},
+{"learn":[0.03328305708],"iteration":517,"passed_time":3.756146439,"remaining_time":3.495101513},
+{"learn":[0.03327622683],"iteration":518,"passed_time":3.76273415,"remaining_time":3.487235311},
+{"learn":[0.0332676599],"iteration":519,"passed_time":3.769431306,"remaining_time":3.479475052},
+{"learn":[0.03325394782],"iteration":520,"passed_time":3.776533425,"remaining_time":3.472091191},
+{"learn":[0.03324567136],"iteration":521,"passed_time":3.783549176,"remaining_time":3.464629322},
+{"learn":[0.03323089745],"iteration":522,"passed_time":3.790229021,"remaining_time":3.456862798},
+{"learn":[0.03322107743],"iteration":523,"passed_time":3.79761783,"remaining_time":3.449744441},
+{"learn":[0.03316435537],"iteration":524,"passed_time":3.80517981,"remaining_time":3.442781733},
+{"learn":[0.03315277754],"iteration":525,"passed_time":3.811985094,"remaining_time":3.435134857},
+{"learn":[0.03314619233],"iteration":526,"passed_time":3.818394826,"remaining_time":3.427136153},
+{"learn":[0.03310415794],"iteration":527,"passed_time":3.825574985,"remaining_time":3.419832183},
+{"learn":[0.03308940035],"iteration":528,"passed_time":3.832390947,"remaining_time":3.412204416},
+{"learn":[0.03299316546],"iteration":529,"passed_time":3.83975,"remaining_time":3.405061321},
+{"learn":[0.03290758896],"iteration":530,"passed_time":3.846962516,"remaining_time":3.397787985},
+{"learn":[0.03289649204],"iteration":531,"passed_time":3.853859113,"remaining_time":3.390236964},
+{"learn":[0.03289079862],"iteration":532,"passed_time":3.860484803,"remaining_time":3.382451038},
+{"learn":[0.03284169565],"iteration":533,"passed_time":3.867734022,"remaining_time":3.375213584},
+{"learn":[0.03281122611],"iteration":534,"passed_time":3.874621088,"remaining_time":3.36766132},
+{"learn":[0.0328030323],"iteration":535,"passed_time":3.881314594,"remaining_time":3.359943977},
+{"learn":[0.0327064234],"iteration":536,"passed_time":3.888594718,"remaining_time":3.352736228},
+{"learn":[0.03261310302],"iteration":537,"passed_time":3.896215456,"remaining_time":3.345820707},
+{"learn":[0.03259689203],"iteration":538,"passed_time":3.902360493,"remaining_time":3.337640422},
+{"learn":[0.03258947864],"iteration":539,"passed_time":3.909671504,"remaining_time":3.330460911},
+{"learn":[0.03258382506],"iteration":540,"passed_time":3.916144256,"remaining_time":3.322569711},
+{"learn":[0.03255166189],"iteration":541,"passed_time":3.923056228,"remaining_time":3.315054894},
+{"learn":[0.03253121396],"iteration":542,"passed_time":3.930294623,"remaining_time":3.307817022},
+{"learn":[0.03239707126],"iteration":543,"passed_time":3.937505861,"remaining_time":3.300556383},
+{"learn":[0.03233488348],"iteration":544,"passed_time":3.94508976,"remaining_time":3.293607047},
+{"learn":[0.03225954025],"iteration":545,"passed_time":3.951942917,"remaining_time":3.286047774},
+{"learn":[0.03215917022],"iteration":546,"passed_time":3.959320222,"remaining_time":3.278925156},
+{"learn":[0.03215066587],"iteration":547,"passed_time":3.965600654,"remaining_time":3.27089689},
+{"learn":[0.03213930065],"iteration":548,"passed_time":3.971804007,"remaining_time":3.262811671},
+{"learn":[0.03212068017],"iteration":549,"passed_time":3.978434344,"remaining_time":3.255082645},
+{"learn":[0.03209629524],"iteration":550,"passed_time":3.985645033,"remaining_time":3.247830526},
+{"learn":[0.03205774208],"iteration":551,"passed_time":3.993028897,"remaining_time":3.240719105},
+{"learn":[0.03203691266],"iteration":552,"passed_time":3.999656914,"remaining_time":3.232995734},
+{"learn":[0.03201495359],"iteration":553,"passed_time":4.007864234,"remaining_time":3.226547741},
+{"learn":[0.03193871108],"iteration":554,"passed_time":4.015591352,"remaining_time":3.219708381},
+{"learn":[0.03190968832],"iteration":555,"passed_time":4.02289195,"remaining_time":3.212525226},
+{"learn":[0.03189641061],"iteration":556,"passed_time":4.029621057,"remaining_time":3.204887124},
+{"learn":[0.03189214839],"iteration":557,"passed_time":4.036115922,"remaining_time":3.197066734},
+{"learn":[0.03188091475],"iteration":558,"passed_time":4.042408162,"remaining_time":3.189091234},
+{"learn":[0.03182915248],"iteration":559,"passed_time":4.049385489,"remaining_time":3.181660027},
+{"learn":[0.03181253278],"iteration":560,"passed_time":4.056282808,"remaining_time":3.17416783},
+{"learn":[0.03176195694],"iteration":561,"passed_time":4.063938494,"remaining_time":3.167268791},
+{"learn":[0.0316978627],"iteration":562,"passed_time":4.071274355,"remaining_time":3.160118816},
+{"learn":[0.03163917423],"iteration":563,"passed_time":4.078649777,"remaining_time":3.152998764},
+{"learn":[0.0315622924],"iteration":564,"passed_time":4.085579757,"remaining_time":3.145534857},
+{"learn":[0.03149615746],"iteration":565,"passed_time":4.092211731,"remaining_time":3.13784433},
+{"learn":[0.03147964054],"iteration":566,"passed_time":4.099062839,"remaining_time":3.130324884},
+{"learn":[0.03144101216],"iteration":567,"passed_time":4.105911159,"remaining_time":3.12280567},
+{"learn":[0.03143160056],"iteration":568,"passed_time":4.113249054,"remaining_time":3.115659653},
+{"learn":[0.03142022449],"iteration":569,"passed_time":4.120905862,"remaining_time":3.108753545},
+{"learn":[0.03139719018],"iteration":570,"passed_time":4.127546897,"remaining_time":3.101081644},
+{"learn":[0.03135256171],"iteration":571,"passed_time":4.134682932,"remaining_time":3.093783733},
+{"learn":[0.03129453851],"iteration":572,"passed_time":4.142497509,"remaining_time":3.086992035},
+{"learn":[0.03127246926],"iteration":573,"passed_time":4.149389754,"remaining_time":3.079512257},
+{"learn":[0.03124860896],"iteration":574,"passed_time":4.156393241,"remaining_time":3.072116743},
+{"learn":[0.03119037052],"iteration":575,"passed_time":4.163603263,"remaining_time":3.064874624},
+{"learn":[0.0311592702],"iteration":576,"passed_time":4.170805293,"remaining_time":3.057626757},
+{"learn":[0.03115136367],"iteration":577,"passed_time":4.176995014,"remaining_time":3.049639958},
+{"learn":[0.0311266516],"iteration":578,"passed_time":4.183438606,"remaining_time":3.04184396},
+{"learn":[0.03112205614],"iteration":579,"passed_time":4.190683783,"remaining_time":3.034633084},
+{"learn":[0.03111395406],"iteration":580,"passed_time":4.196833707,"remaining_time":3.026632226},
+{"learn":[0.0311006962],"iteration":581,"passed_time":4.203668397,"remaining_time":3.019129536},
+{"learn":[0.03109471388],"iteration":582,"passed_time":4.209533314,"remaining_time":3.010935492},
+{"learn":[0.03107083379],"iteration":583,"passed_time":4.216413018,"remaining_time":3.003472287},
+{"learn":[0.03097675709],"iteration":584,"passed_time":4.2234833,"remaining_time":2.996146273},
+{"learn":[0.03096600229],"iteration":585,"passed_time":4.229448704,"remaining_time":2.988040552},
+{"learn":[0.03096158133],"iteration":586,"passed_time":4.236660924,"remaining_time":2.980819355},
+{"learn":[0.03094960337],"iteration":587,"passed_time":4.242948862,"remaining_time":2.972950563},
+{"learn":[0.03094087644],"iteration":588,"passed_time":4.249966141,"remaining_time":2.965596068},
+{"learn":[0.03092797226],"iteration":589,"passed_time":4.256543174,"remaining_time":2.957936782},
+{"learn":[0.03091757006],"iteration":590,"passed_time":4.26244944,"remaining_time":2.949816956},
+{"learn":[0.03086376385],"iteration":591,"passed_time":4.269614188,"remaining_time":2.94257194},
+{"learn":[0.03082948064],"iteration":592,"passed_time":4.276182715,"remaining_time":2.934917985},
+{"learn":[0.03077946147],"iteration":593,"passed_time":4.282944371,"remaining_time":2.927399688},
+{"learn":[0.0307674574],"iteration":594,"passed_time":4.289917295,"remaining_time":2.920027739},
+{"learn":[0.03075791442],"iteration":595,"passed_time":4.296129153,"remaining_time":2.912141238},
+{"learn":[0.03075372426],"iteration":596,"passed_time":4.303025211,"remaining_time":2.904722211},
+{"learn":[0.03070617726],"iteration":597,"passed_time":4.309697674,"remaining_time":2.897154624},
+{"learn":[0.03068149877],"iteration":598,"passed_time":4.316834044,"remaining_time":2.889900587},
+{"learn":[0.03067323112],"iteration":599,"passed_time":4.323653178,"remaining_time":2.882435452},
+{"learn":[0.03066662529],"iteration":600,"passed_time":4.331405757,"remaining_time":2.875592175},
+{"learn":[0.03066212123],"iteration":601,"passed_time":4.337968966,"remaining_time":2.867959549},
+{"learn":[0.03065665474],"iteration":602,"passed_time":4.344772974,"remaining_time":2.860489006},
+{"learn":[0.03065108794],"iteration":603,"passed_time":4.352462437,"remaining_time":2.8536012},
+{"learn":[0.03054826119],"iteration":604,"passed_time":4.359303263,"remaining_time":2.846156676},
+{"learn":[0.03052656921],"iteration":605,"passed_time":4.366474868,"remaining_time":2.838929205},
+{"learn":[0.03043035026],"iteration":606,"passed_time":4.373530543,"remaining_time":2.831626859},
+{"learn":[0.03040204751],"iteration":607,"passed_time":4.38126244,"remaining_time":2.82476131},
+{"learn":[0.03038464911],"iteration":608,"passed_time":4.388052118,"remaining_time":2.817287977},
+{"learn":[0.03031150772],"iteration":609,"passed_time":4.395332914,"remaining_time":2.81013088},
+{"learn":[0.03028674661],"iteration":610,"passed_time":4.402665364,"remaining_time":2.803006263},
+{"learn":[0.03024984829],"iteration":611,"passed_time":4.409467116,"remaining_time":2.795544512},
+{"learn":[0.03017124724],"iteration":612,"passed_time":4.417392021,"remaining_time":2.788793984},
+{"learn":[0.03014600324],"iteration":613,"passed_time":4.423913627,"remaining_time":2.781157427},
+{"learn":[0.03013761028],"iteration":614,"passed_time":4.430035435,"remaining_time":2.773274215},
+{"learn":[0.03012744285],"iteration":615,"passed_time":4.437021125,"remaining_time":2.765935246},
+{"learn":[0.03010411839],"iteration":616,"passed_time":4.44426764,"remaining_time":2.758759329},
+{"learn":[0.03008834154],"iteration":617,"passed_time":4.45108408,"remaining_time":2.751317344},
+{"learn":[0.03003369623],"iteration":618,"passed_time":4.45812865,"remaining_time":2.744017796},
+{"learn":[0.03002495102],"iteration":619,"passed_time":4.464901719,"remaining_time":2.736552666},
+{"learn":[0.02996858568],"iteration":620,"passed_time":4.47161184,"remaining_time":2.729051349},
+{"learn":[0.02996409988],"iteration":621,"passed_time":4.478021595,"remaining_time":2.721370037},
+{"learn":[0.02994894962],"iteration":622,"passed_time":4.485304223,"remaining_time":2.714221015},
+{"learn":[0.02993696216],"iteration":623,"passed_time":4.492143305,"remaining_time":2.706804299},
+{"learn":[0.02992612967],"iteration":624,"passed_time":4.498783659,"remaining_time":2.699270196},
+{"learn":[0.02984927443],"iteration":625,"passed_time":4.5055321,"remaining_time":2.691803523},
+{"learn":[0.02979581469],"iteration":626,"passed_time":4.512101301,"remaining_time":2.684232512},
+{"learn":[0.02976539254],"iteration":627,"passed_time":4.519974474,"remaining_time":2.677437109},
+{"learn":[0.02971011729],"iteration":628,"passed_time":4.52624654,"remaining_time":2.669693905},
+{"learn":[0.02962423052],"iteration":629,"passed_time":4.533378316,"remaining_time":2.662460281},
+{"learn":[0.02960036713],"iteration":630,"passed_time":4.540113636,"remaining_time":2.654995137},
+{"learn":[0.02958940149],"iteration":631,"passed_time":4.546743623,"remaining_time":2.64747097},
+{"learn":[0.02957588507],"iteration":632,"passed_time":4.553873971,"remaining_time":2.640239727},
+{"learn":[0.02951609243],"iteration":633,"passed_time":4.561033382,"remaining_time":2.63302558},
+{"learn":[0.02950680693],"iteration":634,"passed_time":4.567344502,"remaining_time":2.625324005},
+{"learn":[0.02948151137],"iteration":635,"passed_time":4.573829974,"remaining_time":2.617726589},
+{"learn":[0.02947629207],"iteration":636,"passed_time":4.580710488,"remaining_time":2.610357782},
+{"learn":[0.02942817314],"iteration":637,"passed_time":4.587685029,"remaining_time":2.603043857},
+{"learn":[0.02941439677],"iteration":638,"passed_time":4.593783675,"remaining_time":2.595236161},
+{"learn":[0.0293823908],"iteration":639,"passed_time":4.600969547,"remaining_time":2.58804537},
+{"learn":[0.02937342382],"iteration":640,"passed_time":4.607496511,"remaining_time":2.580485566},
+{"learn":[0.02936380125],"iteration":641,"passed_time":4.614904164,"remaining_time":2.573420079},
+{"learn":[0.02935584495],"iteration":642,"passed_time":4.62176944,"remaining_time":2.566052395},
+{"learn":[0.02932434288],"iteration":643,"passed_time":4.628810316,"remaining_time":2.558783343},
+{"learn":[0.029320235],"iteration":644,"passed_time":4.635655641,"remaining_time":2.551407368},
+{"learn":[0.02931039971],"iteration":645,"passed_time":4.642134639,"remaining_time":2.543832294},
+{"learn":[0.02930282704],"iteration":646,"passed_time":4.648974695,"remaining_time":2.5364576},
+{"learn":[0.02927863687],"iteration":647,"passed_time":4.655837515,"remaining_time":2.529096922},
+{"learn":[0.02927081487],"iteration":648,"passed_time":4.662300287,"remaining_time":2.521521419},
+{"learn":[0.02925649888],"iteration":649,"passed_time":4.668971907,"remaining_time":2.514061796},
+{"learn":[0.02921421558],"iteration":650,"passed_time":4.676018997,"remaining_time":2.506805883},
+{"learn":[0.02915158475],"iteration":651,"passed_time":4.683000652,"remaining_time":2.499515685},
+{"learn":[0.02914654608],"iteration":652,"passed_time":4.690419341,"remaining_time":2.49245867},
+{"learn":[0.02913281664],"iteration":653,"passed_time":4.697035984,"remaining_time":2.484976224},
+{"learn":[0.02912856535],"iteration":654,"passed_time":4.703113715,"remaining_time":2.477212567},
+{"learn":[0.02911910739],"iteration":655,"passed_time":4.709611717,"remaining_time":2.469674437},
+{"learn":[0.02909215104],"iteration":656,"passed_time":4.716710683,"remaining_time":2.462453218},
+{"learn":[0.02907713449],"iteration":657,"passed_time":4.723326218,"remaining_time":2.454981104},
+{"learn":[0.02903953506],"iteration":658,"passed_time":4.730021884,"remaining_time":2.447553054},
+{"learn":[0.0290306791],"iteration":659,"passed_time":4.73673047,"remaining_time":2.440133879},
+{"learn":[0.02900995673],"iteration":660,"passed_time":4.743891549,"remaining_time":2.432948919},
+{"learn":[0.02898829763],"iteration":661,"passed_time":4.750705916,"remaining_time":2.425587009},
+{"learn":[0.02897764142],"iteration":662,"passed_time":4.75762107,"remaining_time":2.41827798},
+{"learn":[0.02896859616],"iteration":663,"passed_time":4.764317347,"remaining_time":2.410859381},
+{"learn":[0.02891620509],"iteration":664,"passed_time":4.771188041,"remaining_time":2.403530818},
+{"learn":[0.02888715857],"iteration":665,"passed_time":4.778398348,"remaining_time":2.396373947},
+{"learn":[0.02887788998],"iteration":666,"passed_time":4.785131062,"remaining_time":2.388978476},
+{"learn":[0.02886161088],"iteration":667,"passed_time":4.792112572,"remaining_time":2.381708644},
+{"learn":[0.02883236057],"iteration":668,"passed_time":4.799201211,"remaining_time":2.374492677},
+{"learn":[0.0288141427],"iteration":669,"passed_time":4.805663574,"remaining_time":2.366968626},
+{"learn":[0.02881056941],"iteration":670,"passed_time":4.813104913,"remaining_time":2.359927744},
+{"learn":[0.02878278527],"iteration":671,"passed_time":4.819795639,"remaining_time":2.3525193},
+{"learn":[0.02877417387],"iteration":672,"passed_time":4.826898218,"remaining_time":2.345313101},
+{"learn":[0.02872215364],"iteration":673,"passed_time":4.834062197,"remaining_time":2.338136908},
+{"learn":[0.02870768294],"iteration":674,"passed_time":4.840109704,"remaining_time":2.330423191},
+{"learn":[0.02869909677],"iteration":675,"passed_time":4.847253265,"remaining_time":2.32323973},
+{"learn":[0.02868066708],"iteration":676,"passed_time":4.853606971,"remaining_time":2.315679544},
+{"learn":[0.02859642625],"iteration":677,"passed_time":4.861317104,"remaining_time":2.30876712},
+{"learn":[0.02858811474],"iteration":678,"passed_time":4.867373736,"remaining_time":2.301070647},
+{"learn":[0.02857385585],"iteration":679,"passed_time":4.873487999,"remaining_time":2.293406117},
+{"learn":[0.0285283975],"iteration":680,"passed_time":4.880664008,"remaining_time":2.286243493},
+{"learn":[0.02851158389],"iteration":681,"passed_time":4.888164389,"remaining_time":2.279232076},
+{"learn":[0.02849337391],"iteration":682,"passed_time":4.89573927,"remaining_time":2.272253805},
+{"learn":[0.02846595106],"iteration":683,"passed_time":4.902942552,"remaining_time":2.265102115},
+{"learn":[0.028456776],"iteration":684,"passed_time":4.909476796,"remaining_time":2.257642614},
+{"learn":[0.02842819638],"iteration":685,"passed_time":4.916144026,"remaining_time":2.250246682},
+{"learn":[0.02842323692],"iteration":686,"passed_time":4.923047773,"remaining_time":2.24296063},
+{"learn":[0.02841313969],"iteration":687,"passed_time":4.929641571,"remaining_time":2.235535131},
+{"learn":[0.02840326324],"iteration":688,"passed_time":4.936553667,"remaining_time":2.228255719},
+{"learn":[0.02833955018],"iteration":689,"passed_time":4.943741762,"remaining_time":2.221101371},
+{"learn":[0.02832629289],"iteration":690,"passed_time":4.950518638,"remaining_time":2.213763038},
+{"learn":[0.02828993795],"iteration":691,"passed_time":4.957711635,"remaining_time":2.206611537},
+{"learn":[0.02828577645],"iteration":692,"passed_time":4.965008786,"remaining_time":2.199506057},
+{"learn":[0.02827501951],"iteration":693,"passed_time":4.971508933,"remaining_time":2.192048607},
+{"learn":[0.02826778187],"iteration":694,"passed_time":4.977820627,"remaining_time":2.18451121},
+{"learn":[0.02823814298],"iteration":695,"passed_time":4.984788389,"remaining_time":2.177263894},
+{"learn":[0.0282299856],"iteration":696,"passed_time":4.991593789,"remaining_time":2.169946798},
+{"learn":[0.02822046234],"iteration":697,"passed_time":4.998787033,"remaining_time":2.162798974},
+{"learn":[0.02821535659],"iteration":698,"passed_time":5.005252805,"remaining_time":2.15533776},
+{"learn":[0.0282085824],"iteration":699,"passed_time":5.01225094,"remaining_time":2.148107546},
+{"learn":[0.02820022063],"iteration":700,"passed_time":5.018631693,"remaining_time":2.14061466},
+{"learn":[0.0281952966],"iteration":701,"passed_time":5.025847074,"remaining_time":2.133479242},
+{"learn":[0.02815534324],"iteration":702,"passed_time":5.032683298,"remaining_time":2.126183413},
+{"learn":[0.02815162679],"iteration":703,"passed_time":5.039417736,"remaining_time":2.118846094},
+{"learn":[0.02811759191],"iteration":704,"passed_time":5.046682908,"remaining_time":2.111732564},
+{"learn":[0.02801055464],"iteration":705,"passed_time":5.053913728,"remaining_time":2.104604301},
+{"learn":[0.02798581971],"iteration":706,"passed_time":5.062003765,"remaining_time":2.097831829},
+{"learn":[0.02797382773],"iteration":707,"passed_time":5.068096659,"remaining_time":2.090231955},
+{"learn":[0.02794370389],"iteration":708,"passed_time":5.075272606,"remaining_time":2.083080858},
+{"learn":[0.02793705349],"iteration":709,"passed_time":5.081668563,"remaining_time":2.075611103},
+{"learn":[0.02793237697],"iteration":710,"passed_time":5.088474587,"remaining_time":2.068311049},
+{"learn":[0.02792762848],"iteration":711,"passed_time":5.094818493,"remaining_time":2.060825458},
+{"learn":[0.02791303954],"iteration":712,"passed_time":5.101104579,"remaining_time":2.053319795},
+{"learn":[0.02785980061],"iteration":713,"passed_time":5.108606632,"remaining_time":2.046304617},
+{"learn":[0.02779280862],"iteration":714,"passed_time":5.115698098,"remaining_time":2.039124417},
+{"learn":[0.02775204778],"iteration":715,"passed_time":5.123333727,"remaining_time":2.032160305},
+{"learn":[0.02772187542],"iteration":716,"passed_time":5.129528508,"remaining_time":2.024625618},
+{"learn":[0.02763956462],"iteration":717,"passed_time":5.137448205,"remaining_time":2.017772136},
+{"learn":[0.02760563202],"iteration":718,"passed_time":5.14491421,"remaining_time":2.010738377},
+{"learn":[0.02758605921],"iteration":719,"passed_time":5.151658144,"remaining_time":2.003422612},
+{"learn":[0.02757958131],"iteration":720,"passed_time":5.158511689,"remaining_time":1.996150848},
+{"learn":[0.02754817283],"iteration":721,"passed_time":5.165991224,"remaining_time":1.989121275},
+{"learn":[0.02745633667],"iteration":722,"passed_time":5.17376162,"remaining_time":1.982201893},
+{"learn":[0.02744621287],"iteration":723,"passed_time":5.180681265,"remaining_time":1.974955841},
+{"learn":[0.02743602837],"iteration":724,"passed_time":5.187549527,"remaining_time":1.9676912},
+{"learn":[0.027426361],"iteration":725,"passed_time":5.194809544,"remaining_time":1.960575503},
+{"learn":[0.02741889055],"iteration":726,"passed_time":5.201268078,"remaining_time":1.953158439},
+{"learn":[0.02741198924],"iteration":727,"passed_time":5.208939676,"remaining_time":1.946197242},
+{"learn":[0.02738993344],"iteration":728,"passed_time":5.216061725,"remaining_time":1.939029805},
+{"learn":[0.02728424825],"iteration":729,"passed_time":5.22337696,"remaining_time":1.931933944},
+{"learn":[0.02728125614],"iteration":730,"passed_time":5.229827586,"remaining_time":1.924519317},
+{"learn":[0.02725893063],"iteration":731,"passed_time":5.236347024,"remaining_time":1.917132517},
+{"learn":[0.02723869636],"iteration":732,"passed_time":5.243237409,"remaining_time":1.909883203},
+{"learn":[0.02716161257],"iteration":733,"passed_time":5.250047861,"remaining_time":1.902605901},
+{"learn":[0.02713828064],"iteration":734,"passed_time":5.25711278,"remaining_time":1.895421615},
+{"learn":[0.02713171714],"iteration":735,"passed_time":5.263828872,"remaining_time":1.88811253},
+{"learn":[0.02711962197],"iteration":736,"passed_time":5.270723043,"remaining_time":1.880868603},
+{"learn":[0.02711462755],"iteration":737,"passed_time":5.278014639,"remaining_time":1.873766715},
+{"learn":[0.02706637228],"iteration":738,"passed_time":5.285297041,"remaining_time":1.866661066},
+{"learn":[0.02699547895],"iteration":739,"passed_time":5.292529302,"remaining_time":1.859537322},
+{"learn":[0.02699189104],"iteration":740,"passed_time":5.298843711,"remaining_time":1.852092471},
+{"learn":[0.02695623953],"iteration":741,"passed_time":5.305908846,"remaining_time":1.844911701},
+{"learn":[0.02694306696],"iteration":742,"passed_time":5.312986626,"remaining_time":1.837735616},
+{"learn":[0.0269246898],"iteration":743,"passed_time":5.320147792,"remaining_time":1.830588488},
+{"learn":[0.02691441808],"iteration":744,"passed_time":5.326530623,"remaining_time":1.823174911},
+{"learn":[0.02687652898],"iteration":745,"passed_time":5.333941965,"remaining_time":1.816114288},
+{"learn":[0.02685505766],"iteration":746,"passed_time":5.341253475,"remaining_time":1.809018914},
+{"learn":[0.02684906965],"iteration":747,"passed_time":5.347628862,"remaining_time":1.801607585},
+{"learn":[0.02682367574],"iteration":748,"passed_time":5.354926535,"remaining_time":1.794508091},
+{"learn":[0.02681755825],"iteration":749,"passed_time":5.362311366,"remaining_time":1.787437122},
+{"learn":[0.02680065202],"iteration":750,"passed_time":5.369474226,"remaining_time":1.780291721},
+{"learn":[0.02678964429],"iteration":751,"passed_time":5.376775338,"remaining_time":1.773191867},
+{"learn":[0.0267367592],"iteration":752,"passed_time":5.383974924,"remaining_time":1.766058176},
+{"learn":[0.02669856172],"iteration":753,"passed_time":5.391259228,"remaining_time":1.75895195},
+{"learn":[0.02669144291],"iteration":754,"passed_time":5.398062889,"remaining_time":1.751689282},
+{"learn":[0.02668775657],"iteration":755,"passed_time":5.405009103,"remaining_time":1.744473837},
+{"learn":[0.02668440948],"iteration":756,"passed_time":5.41131961,"remaining_time":1.73705504},
+{"learn":[0.02659284947],"iteration":757,"passed_time":5.41912995,"remaining_time":1.730118005},
+{"learn":[0.02657445689],"iteration":758,"passed_time":5.425985329,"remaining_time":1.722875447},
+{"learn":[0.02656470179],"iteration":759,"passed_time":5.432094909,"remaining_time":1.715398392},
+{"learn":[0.02653963194],"iteration":760,"passed_time":5.4392989,"remaining_time":1.708268643},
+{"learn":[0.02653270889],"iteration":761,"passed_time":5.44572489,"remaining_time":1.7008957},
+{"learn":[0.02650442012],"iteration":762,"passed_time":5.453093941,"remaining_time":1.69381817},
+{"learn":[0.02645699797],"iteration":763,"passed_time":5.459756919,"remaining_time":1.686521771},
+{"learn":[0.02636849252],"iteration":764,"passed_time":5.467024885,"remaining_time":1.679412873},
+{"learn":[0.02636469683],"iteration":765,"passed_time":5.473595214,"remaining_time":1.672090444},
+{"learn":[0.02635664192],"iteration":766,"passed_time":5.480042477,"remaining_time":1.664732591},
+{"learn":[0.02632323718],"iteration":767,"passed_time":5.48762931,"remaining_time":1.657721354},
+{"learn":[0.02631477653],"iteration":768,"passed_time":5.493637074,"remaining_time":1.650234284},
+{"learn":[0.02628811693],"iteration":769,"passed_time":5.500609046,"remaining_time":1.643039066},
+{"learn":[0.02626957332],"iteration":770,"passed_time":5.507653626,"remaining_time":1.635865993},
+{"learn":[0.0262651055],"iteration":771,"passed_time":5.514370097,"remaining_time":1.62859635},
+{"learn":[0.02625774839],"iteration":772,"passed_time":5.521151286,"remaining_time":1.621347143},
+{"learn":[0.02624689512],"iteration":773,"passed_time":5.527559602,"remaining_time":1.613990271},
+{"learn":[0.02619720299],"iteration":774,"passed_time":5.534653925,"remaining_time":1.606835011},
+{"learn":[0.0261870716],"iteration":775,"passed_time":5.54138859,"remaining_time":1.599576088},
+{"learn":[0.02618333886],"iteration":776,"passed_time":5.548206534,"remaining_time":1.592342416},
+{"learn":[0.02614901722],"iteration":777,"passed_time":5.5554416,"remaining_time":1.585228837},
+{"learn":[0.02613471676],"iteration":778,"passed_time":5.562022237,"remaining_time":1.577929287},
+{"learn":[0.02611262808],"iteration":779,"passed_time":5.568918487,"remaining_time":1.570720599},
+{"learn":[0.02611046878],"iteration":780,"passed_time":5.575938263,"remaining_time":1.563547349},
+{"learn":[0.02609893965],"iteration":781,"passed_time":5.582561015,"remaining_time":1.556263812},
+{"learn":[0.02607244396],"iteration":782,"passed_time":5.589725047,"remaining_time":1.549131973},
+{"learn":[0.02602443608],"iteration":783,"passed_time":5.597082113,"remaining_time":1.542053235},
+{"learn":[0.02600695947],"iteration":784,"passed_time":5.604402873,"remaining_time":1.534963844},
+{"learn":[0.02599514107],"iteration":785,"passed_time":5.611334116,"remaining_time":1.527767813},
+{"learn":[0.02597510569],"iteration":786,"passed_time":5.618358046,"remaining_time":1.52059754},
+{"learn":[0.02594647083],"iteration":787,"passed_time":5.624610138,"remaining_time":1.513219986},
+{"learn":[0.02594195753],"iteration":788,"passed_time":5.630730953,"remaining_time":1.505810179},
+{"learn":[0.02591110424],"iteration":789,"passed_time":5.638131726,"remaining_time":1.498743876},
+{"learn":[0.02586411329],"iteration":790,"passed_time":5.645292702,"remaining_time":1.491613369},
+{"learn":[0.02583741607],"iteration":791,"passed_time":5.652265339,"remaining_time":1.484433321},
+{"learn":[0.02581581331],"iteration":792,"passed_time":5.659264673,"remaining_time":1.477260766},
+{"learn":[0.02580876397],"iteration":793,"passed_time":5.666309749,"remaining_time":1.470100514},
+{"learn":[0.02579990459],"iteration":794,"passed_time":5.673092925,"remaining_time":1.462873018},
+{"learn":[0.02570221924],"iteration":795,"passed_time":5.68003948,"remaining_time":1.45568851},
+{"learn":[0.02567624045],"iteration":796,"passed_time":5.686863179,"remaining_time":1.448473307},
+{"learn":[0.02565669234],"iteration":797,"passed_time":5.694055465,"remaining_time":1.441352386},
+{"learn":[0.02565196031],"iteration":798,"passed_time":5.700888655,"remaining_time":1.434140951},
+{"learn":[0.02564126793],"iteration":799,"passed_time":5.707491462,"remaining_time":1.426872865},
+{"learn":[0.02562263526],"iteration":800,"passed_time":5.714555269,"remaining_time":1.419720972},
+{"learn":[0.02561330565],"iteration":801,"passed_time":5.721290489,"remaining_time":1.412488175},
+{"learn":[0.02560338215],"iteration":802,"passed_time":5.727816902,"remaining_time":1.405205392},
+{"learn":[0.0255991496],"iteration":803,"passed_time":5.734120821,"remaining_time":1.39787025},
+{"learn":[0.02559316325],"iteration":804,"passed_time":5.740751373,"remaining_time":1.390616792},
+{"learn":[0.02558136803],"iteration":805,"passed_time":5.747152341,"remaining_time":1.383309621},
+{"learn":[0.02557230731],"iteration":806,"passed_time":5.753988687,"remaining_time":1.376108819},
+{"learn":[0.02556862501],"iteration":807,"passed_time":5.760827151,"remaining_time":1.368909422},
+{"learn":[0.02549890541],"iteration":808,"passed_time":5.768615883,"remaining_time":1.36193527},
+{"learn":[0.02549189489],"iteration":809,"passed_time":5.775319969,"remaining_time":1.354704684},
+{"learn":[0.02548783973],"iteration":810,"passed_time":5.782009617,"remaining_time":1.347472032},
+{"learn":[0.02546882203],"iteration":811,"passed_time":5.78946418,"remaining_time":1.340417815},
+{"learn":[0.02544718682],"iteration":812,"passed_time":5.796499666,"remaining_time":1.333266221},
+{"learn":[0.02544185907],"iteration":813,"passed_time":5.803880151,"remaining_time":1.326193744},
+{"learn":[0.02543005094],"iteration":814,"passed_time":5.810529174,"remaining_time":1.318954475},
+{"learn":[0.02542619235],"iteration":815,"passed_time":5.817600197,"remaining_time":1.311811809},
+{"learn":[0.02541820789],"iteration":816,"passed_time":5.824036107,"remaining_time":1.30452706},
+{"learn":[0.0254127645],"iteration":817,"passed_time":5.831042516,"remaining_time":1.297371318},
+{"learn":[0.02540116476],"iteration":818,"passed_time":5.837341958,"remaining_time":1.2900597},
+{"learn":[0.02538324342],"iteration":819,"passed_time":5.843896455,"remaining_time":1.282806539},
+{"learn":[0.02535526742],"iteration":820,"passed_time":5.851425715,"remaining_time":1.275767604},
+{"learn":[0.02531657161],"iteration":821,"passed_time":5.858968249,"remaining_time":1.268730351},
+{"learn":[0.02531080769],"iteration":822,"passed_time":5.865981745,"remaining_time":1.261578091},
+{"learn":[0.02530550836],"iteration":823,"passed_time":5.872664649,"remaining_time":1.254355556},
+{"learn":[0.0252958085],"iteration":824,"passed_time":5.879348409,"remaining_time":1.247134511},
+{"learn":[0.02528371888],"iteration":825,"passed_time":5.88645882,"remaining_time":1.240004643},
+{"learn":[0.02526385979],"iteration":826,"passed_time":5.893368444,"remaining_time":1.232832818},
+{"learn":[0.02524302459],"iteration":827,"passed_time":5.900601169,"remaining_time":1.225728745},
+{"learn":[0.02523333086],"iteration":828,"passed_time":5.907087186,"remaining_time":1.218470336},
+{"learn":[0.02522294582],"iteration":829,"passed_time":5.91444269,"remaining_time":1.211391876},
+{"learn":[0.02519052206],"iteration":830,"passed_time":5.921951384,"remaining_time":1.204343904},
+{"learn":[0.02518401644],"iteration":831,"passed_time":5.928749402,"remaining_time":1.197151322},
+{"learn":[0.02515756447],"iteration":832,"passed_time":5.936216348,"remaining_time":1.190093794},
+{"learn":[0.02515410283],"iteration":833,"passed_time":5.943316671,"remaining_time":1.182962311},
+{"learn":[0.02513777417],"iteration":834,"passed_time":5.950371729,"remaining_time":1.175821959},
+{"learn":[0.02513110809],"iteration":835,"passed_time":5.956726732,"remaining_time":1.168544479},
+{"learn":[0.02512389493],"iteration":836,"passed_time":5.96306295,"remaining_time":1.161265545},
+{"learn":[0.0251111454],"iteration":837,"passed_time":5.969486614,"remaining_time":1.154005765},
+{"learn":[0.02508678731],"iteration":838,"passed_time":5.976500362,"remaining_time":1.146861214},
+{"learn":[0.02508231731],"iteration":839,"passed_time":5.983505261,"remaining_time":1.139715288},
+{"learn":[0.02506235829],"iteration":840,"passed_time":5.990189407,"remaining_time":1.132509056},
+{"learn":[0.0250580117],"iteration":841,"passed_time":5.997425244,"remaining_time":1.125407587},
+{"learn":[0.02502469503],"iteration":842,"passed_time":6.004605778,"remaining_time":1.118295501},
+{"learn":[0.0250083634],"iteration":843,"passed_time":6.011733738,"remaining_time":1.111173535},
+{"learn":[0.02499158274],"iteration":844,"passed_time":6.018416751,"remaining_time":1.103969937},
+{"learn":[0.02495413124],"iteration":845,"passed_time":6.025777128,"remaining_time":1.096890872},
+{"learn":[0.024944665],"iteration":846,"passed_time":6.032157725,"remaining_time":1.089634158},
+{"learn":[0.02491248278],"iteration":847,"passed_time":6.038730866,"remaining_time":1.082414023},
+{"learn":[0.02489625508],"iteration":848,"passed_time":6.045862858,"remaining_time":1.075294807},
+{"learn":[0.02486796749],"iteration":849,"passed_time":6.052520601,"remaining_time":1.068091871},
+{"learn":[0.02486130916],"iteration":850,"passed_time":6.059124616,"remaining_time":1.060880808},
+{"learn":[0.0248507132],"iteration":851,"passed_time":6.066215621,"remaining_time":1.053755765},
+{"learn":[0.02480442923],"iteration":852,"passed_time":6.073295129,"remaining_time":1.046628821},
+{"learn":[0.02478168926],"iteration":853,"passed_time":6.079869134,"remaining_time":1.039415566},
+{"learn":[0.02477237341],"iteration":854,"passed_time":6.086753928,"remaining_time":1.032256514},
+{"learn":[0.0247653735],"iteration":855,"passed_time":6.094067038,"remaining_time":1.025170156},
+{"learn":[0.02476165804],"iteration":856,"passed_time":6.100758445,"remaining_time":1.01797953},
+{"learn":[0.02474681606],"iteration":857,"passed_time":6.108480577,"remaining_time":1.010960655},
+{"learn":[0.0247392133],"iteration":858,"passed_time":6.115661463,"remaining_time":1.0038513},
+{"learn":[0.0247334647],"iteration":859,"passed_time":6.122177294,"remaining_time":0.996633513},
+{"learn":[0.02472781995],"iteration":860,"passed_time":6.129189376,"remaining_time":0.9894974718},
+{"learn":[0.02472404596],"iteration":861,"passed_time":6.135643046,"remaining_time":0.9822723206},
+{"learn":[0.02471132637],"iteration":862,"passed_time":6.143110647,"remaining_time":0.9752099173},
+{"learn":[0.02470461834],"iteration":863,"passed_time":6.149470882,"remaining_time":0.9679722684},
+{"learn":[0.02466474784],"iteration":864,"passed_time":6.15639226,"remaining_time":0.9608242255},
+{"learn":[0.02463549014],"iteration":865,"passed_time":6.16365934,"remaining_time":0.953730198},
+{"learn":[0.02459751632],"iteration":866,"passed_time":6.170663745,"remaining_time":0.9465954764},
+{"learn":[0.02456658494],"iteration":867,"passed_time":6.178222266,"remaining_time":0.9395453216},
+{"learn":[0.0245349431],"iteration":868,"passed_time":6.184993824,"remaining_time":0.9323753635},
+{"learn":[0.02453181104],"iteration":869,"passed_time":6.192525623,"remaining_time":0.9253199207},
+{"learn":[0.02452710158],"iteration":870,"passed_time":6.199040145,"remaining_time":0.9181127196},
+{"learn":[0.02451645205],"iteration":871,"passed_time":6.206460529,"remaining_time":0.9110400776},
+{"learn":[0.02448830075],"iteration":872,"passed_time":6.213384982,"remaining_time":0.9038944934},
+{"learn":[0.02447869069],"iteration":873,"passed_time":6.219786728,"remaining_time":0.8966740591},
+{"learn":[0.02446320843],"iteration":874,"passed_time":6.226445939,"remaining_time":0.8894922769},
+{"learn":[0.02445766002],"iteration":875,"passed_time":6.233039306,"remaining_time":0.8823023676},
+{"learn":[0.02444557097],"iteration":876,"passed_time":6.239933832,"remaining_time":0.8751560562},
+{"learn":[0.02440709318],"iteration":877,"passed_time":6.246780856,"remaining_time":0.8680037181},
+{"learn":[0.02439801428],"iteration":878,"passed_time":6.253574434,"remaining_time":0.8608447173},
+{"learn":[0.02439102947],"iteration":879,"passed_time":6.26036533,"remaining_time":0.8536861813},
+{"learn":[0.02438700937],"iteration":880,"passed_time":6.266584203,"remaining_time":0.8464512148},
+{"learn":[0.0243830278],"iteration":881,"passed_time":6.273132795,"remaining_time":0.8392626641},
+{"learn":[0.02437976675],"iteration":882,"passed_time":6.279786242,"remaining_time":0.8320894568},
+{"learn":[0.02436996739],"iteration":883,"passed_time":6.286498815,"remaining_time":0.8249251838},
+{"learn":[0.0243662823],"iteration":884,"passed_time":6.293112616,"remaining_time":0.817749097},
+{"learn":[0.02436277412],"iteration":885,"passed_time":6.299147452,"remaining_time":0.8104997851},
+{"learn":[0.02434522499],"iteration":886,"passed_time":6.305885612,"remaining_time":0.8033428119},
+{"learn":[0.0243318236],"iteration":887,"passed_time":6.312831516,"remaining_time":0.796212984},
+{"learn":[0.02429761963],"iteration":888,"passed_time":6.320398485,"remaining_time":0.7891611156},
+{"learn":[0.02429392789],"iteration":889,"passed_time":6.327949339,"remaining_time":0.7821060981},
+{"learn":[0.02428605805],"iteration":890,"passed_time":6.334433836,"remaining_time":0.7749195152},
+{"learn":[0.02427827978],"iteration":891,"passed_time":6.341226477,"remaining_time":0.7677718156},
+{"learn":[0.02425750782],"iteration":892,"passed_time":6.348352662,"remaining_time":0.7606648766},
+{"learn":[0.02425173856],"iteration":893,"passed_time":6.355320075,"remaining_time":0.7535390693},
+{"learn":[0.02424258499],"iteration":894,"passed_time":6.362088615,"remaining_time":0.7463902845},
+{"learn":[0.02420970418],"iteration":895,"passed_time":6.369190317,"remaining_time":0.7392810189},
+{"learn":[0.02420415676],"iteration":896,"passed_time":6.376432957,"remaining_time":0.7321879539},
+{"learn":[0.02418282221],"iteration":897,"passed_time":6.384542003,"remaining_time":0.725192967},
+{"learn":[0.02415830608],"iteration":898,"passed_time":6.392253135,"remaining_time":0.7181507972},
+{"learn":[0.02413690952],"iteration":899,"passed_time":6.399240807,"remaining_time":0.7110267563},
+{"learn":[0.02405252518],"iteration":900,"passed_time":6.406841126,"remaining_time":0.7039703347},
+{"learn":[0.02403662952],"iteration":901,"passed_time":6.413839327,"remaining_time":0.6968472883},
+{"learn":[0.02402495753],"iteration":902,"passed_time":6.42078195,"remaining_time":0.6897185483},
+{"learn":[0.02401868732],"iteration":903,"passed_time":6.42775285,"remaining_time":0.682593223},
+{"learn":[0.02401365048],"iteration":904,"passed_time":6.433779367,"remaining_time":0.6753691049},
+{"learn":[0.02401053154],"iteration":905,"passed_time":6.440719499,"remaining_time":0.6682424204},
+{"learn":[0.0240077297],"iteration":906,"passed_time":6.446855128,"remaining_time":0.661033657},
+{"learn":[0.02397283153],"iteration":907,"passed_time":6.454365177,"remaining_time":0.6539665157},
+{"learn":[0.02395709503],"iteration":908,"passed_time":6.461176434,"remaining_time":0.6468284439},
+{"learn":[0.02390952947],"iteration":909,"passed_time":6.468014762,"remaining_time":0.6396937677},
+{"learn":[0.02390072237],"iteration":910,"passed_time":6.475012907,"remaining_time":0.6325753553},
+{"learn":[0.02389324751],"iteration":911,"passed_time":6.481602193,"remaining_time":0.6254177554},
+{"learn":[0.02388711252],"iteration":912,"passed_time":6.48848207,"remaining_time":0.6182890911},
+{"learn":[0.02388240358],"iteration":913,"passed_time":6.495141098,"remaining_time":0.6111401908},
+{"learn":[0.02383856501],"iteration":914,"passed_time":6.502400299,"remaining_time":0.6040481152},
+{"learn":[0.02380399295],"iteration":915,"passed_time":6.510198148,"remaining_time":0.5970050703},
+{"learn":[0.02379818277],"iteration":916,"passed_time":6.517237991,"remaining_time":0.5898917701},
+{"learn":[0.02379369427],"iteration":917,"passed_time":6.524563779,"remaining_time":0.582804172},
+{"learn":[0.0237862419],"iteration":918,"passed_time":6.53113967,"remaining_time":0.57564996},
+{"learn":[0.02377702495],"iteration":919,"passed_time":6.538523465,"remaining_time":0.5685672578},
+{"learn":[0.02377412791],"iteration":920,"passed_time":6.545409825,"remaining_time":0.5614412336},
+{"learn":[0.02376901607],"iteration":921,"passed_time":6.551982077,"remaining_time":0.5542891562},
+{"learn":[0.02376484466],"iteration":922,"passed_time":6.558534023,"remaining_time":0.5471366412},
+{"learn":[0.02374952939],"iteration":923,"passed_time":6.565708697,"remaining_time":0.540036646},
+{"learn":[0.02373117357],"iteration":924,"passed_time":6.571930064,"remaining_time":0.5328591943},
+{"learn":[0.02372463527],"iteration":925,"passed_time":6.578481684,"remaining_time":0.5257101994},
+{"learn":[0.02366769968],"iteration":926,"passed_time":6.586119462,"remaining_time":0.5186480267},
+{"learn":[0.02366379669],"iteration":927,"passed_time":6.592599975,"remaining_time":0.5114948257},
+{"learn":[0.02364036456],"iteration":928,"passed_time":6.60004434,"remaining_time":0.5044167364},
+{"learn":[0.02362875696],"iteration":929,"passed_time":6.607754205,"remaining_time":0.4973578434},
+{"learn":[0.02361197317],"iteration":930,"passed_time":6.614310999,"remaining_time":0.4902120934},
+{"learn":[0.02360711158],"iteration":931,"passed_time":6.621315211,"remaining_time":0.4831002515},
+{"learn":[0.02358730033],"iteration":932,"passed_time":6.628725089,"remaining_time":0.4760177716},
+{"learn":[0.02357156117],"iteration":933,"passed_time":6.636887472,"remaining_time":0.4689877657},
+{"learn":[0.02356127163],"iteration":934,"passed_time":6.643567166,"remaining_time":0.4618522629},
+{"learn":[0.02354210757],"iteration":935,"passed_time":6.650766551,"remaining_time":0.4547532684},
+{"learn":[0.02352752711],"iteration":936,"passed_time":6.6577784,"remaining_time":0.4476414506},
+{"learn":[0.02351458274],"iteration":937,"passed_time":6.664386312,"remaining_time":0.4405031464},
+{"learn":[0.02349428298],"iteration":938,"passed_time":6.671432344,"remaining_time":0.4333944335},
+{"learn":[0.02347219413],"iteration":939,"passed_time":6.678653558,"remaining_time":0.4262970356},
+{"learn":[0.02345135964],"iteration":940,"passed_time":6.68596361,"remaining_time":0.4192049447},
+{"learn":[0.02342243826],"iteration":941,"passed_time":6.693151072,"remaining_time":0.4121048431},
+{"learn":[0.02340197366],"iteration":942,"passed_time":6.70030678,"remaining_time":0.4050026368},
+{"learn":[0.0233883498],"iteration":943,"passed_time":6.707393466,"remaining_time":0.3978962226},
+{"learn":[0.02337676598],"iteration":944,"passed_time":6.714220872,"remaining_time":0.3907747598},
+{"learn":[0.02335305171],"iteration":945,"passed_time":6.721621296,"remaining_time":0.3836866279},
+{"learn":[0.02334969302],"iteration":946,"passed_time":6.727963186,"remaining_time":0.3765385944},
+{"learn":[0.02333328615],"iteration":947,"passed_time":6.734595584,"remaining_time":0.3694081966},
+{"learn":[0.02331343611],"iteration":948,"passed_time":6.741298775,"remaining_time":0.3622826528},
+{"learn":[0.02330509052],"iteration":949,"passed_time":6.748535919,"remaining_time":0.355186101},
+{"learn":[0.02329027449],"iteration":950,"passed_time":6.756133071,"remaining_time":0.3481078028},
+{"learn":[0.02327422111],"iteration":951,"passed_time":6.762719783,"remaining_time":0.3409774681},
+{"learn":[0.02326776933],"iteration":952,"passed_time":6.769439562,"remaining_time":0.3338548367},
+{"learn":[0.02325271865],"iteration":953,"passed_time":6.776450953,"remaining_time":0.326747111},
+{"learn":[0.02324576803],"iteration":954,"passed_time":6.784006345,"remaining_time":0.3196652204},
+{"learn":[0.02323700398],"iteration":955,"passed_time":6.791289929,"remaining_time":0.3125698294},
+{"learn":[0.02318588118],"iteration":956,"passed_time":6.799078286,"remaining_time":0.3054967255},
+{"learn":[0.02317308766],"iteration":957,"passed_time":6.806084326,"remaining_time":0.2983878306},
+{"learn":[0.02316545401],"iteration":958,"passed_time":6.812453248,"remaining_time":0.2912519115},
+{"learn":[0.02314997662],"iteration":959,"passed_time":6.819546353,"remaining_time":0.2841477647},
+{"learn":[0.02314249514],"iteration":960,"passed_time":6.826078316,"remaining_time":0.2770208682},
+{"learn":[0.02313902133],"iteration":961,"passed_time":6.83306662,"remaining_time":0.2699132345},
+{"learn":[0.02313148571],"iteration":962,"passed_time":6.839829427,"remaining_time":0.2627971846},
+{"learn":[0.02309615497],"iteration":963,"passed_time":6.846663556,"remaining_time":0.2556845311},
+{"learn":[0.02308552725],"iteration":964,"passed_time":6.853880927,"remaining_time":0.2485863549},
+{"learn":[0.02306858804],"iteration":965,"passed_time":6.861379953,"remaining_time":0.2414978451},
+{"learn":[0.02300349215],"iteration":966,"passed_time":6.869354661,"remaining_time":0.2344247195},
+{"learn":[0.0229939654],"iteration":967,"passed_time":6.875609176,"remaining_time":0.2272928653},
+{"learn":[0.02297702085],"iteration":968,"passed_time":6.883715904,"remaining_time":0.2202220774},
+{"learn":[0.02296994833],"iteration":969,"passed_time":6.890282266,"remaining_time":0.2131015134},
+{"learn":[0.02296436766],"iteration":970,"passed_time":6.896468703,"remaining_time":0.205970744},
+{"learn":[0.02296025073],"iteration":971,"passed_time":6.903701639,"remaining_time":0.1988720637},
+{"learn":[0.0229512616],"iteration":972,"passed_time":6.910611489,"remaining_time":0.191764142},
+{"learn":[0.02293930675],"iteration":973,"passed_time":6.917590719,"remaining_time":0.1846584792},
+{"learn":[0.02291980757],"iteration":974,"passed_time":6.924867017,"remaining_time":0.1775606927},
+{"learn":[0.02291633192],"iteration":975,"passed_time":6.931992061,"remaining_time":0.1704588212},
+{"learn":[0.02290005426],"iteration":976,"passed_time":6.938430547,"remaining_time":0.1633407396},
+{"learn":[0.02289727501],"iteration":977,"passed_time":6.945661923,"remaining_time":0.1562418838},
+{"learn":[0.02287880829],"iteration":978,"passed_time":6.953046922,"remaining_time":0.1491460525},
+{"learn":[0.02285149379],"iteration":979,"passed_time":6.960110037,"remaining_time":0.142043062},
+{"learn":[0.02284379327],"iteration":980,"passed_time":6.967162954,"remaining_time":0.1349399553},
+{"learn":[0.02283966579],"iteration":981,"passed_time":6.973394407,"remaining_time":0.1278218934},
+{"learn":[0.02283217514],"iteration":982,"passed_time":6.979918879,"remaining_time":0.1207107029},
+{"learn":[0.02281227017],"iteration":983,"passed_time":6.986239925,"remaining_time":0.1135973972},
+{"learn":[0.02278541809],"iteration":984,"passed_time":6.993431446,"remaining_time":0.106498956},
+{"learn":[0.02277400324],"iteration":985,"passed_time":6.999961327,"remaining_time":0.09939093162},
+{"learn":[0.02276918683],"iteration":986,"passed_time":7.006553307,"remaining_time":0.09228489664},
+{"learn":[0.02276296819],"iteration":987,"passed_time":7.014064195,"remaining_time":0.0851910631},
+{"learn":[0.02274521284],"iteration":988,"passed_time":7.021192248,"remaining_time":0.07809212814},
+{"learn":[0.02272135264],"iteration":989,"passed_time":7.030844042,"remaining_time":0.07101862669},
+{"learn":[0.02271125485],"iteration":990,"passed_time":7.039923089,"remaining_time":0.06393472029},
+{"learn":[0.02270433257],"iteration":991,"passed_time":7.048032971,"remaining_time":0.05683897558},
+{"learn":[0.02269727004],"iteration":992,"passed_time":7.055998407,"remaining_time":0.04974017004},
+{"learn":[0.02268913566],"iteration":993,"passed_time":7.063363832,"remaining_time":0.04263599898},
+{"learn":[0.02267941527],"iteration":994,"passed_time":7.070620738,"remaining_time":0.03553075748},
+{"learn":[0.02266977305],"iteration":995,"passed_time":7.076945174,"remaining_time":0.02842146656},
+{"learn":[0.02266067452],"iteration":996,"passed_time":7.083834855,"remaining_time":0.02131545092},
+{"learn":[0.02264972592],"iteration":997,"passed_time":7.090776168,"remaining_time":0.01420997228},
+{"learn":[0.02264699173],"iteration":998,"passed_time":7.097176165,"remaining_time":0.007104280445},
+{"learn":[0.02264030443],"iteration":999,"passed_time":7.103728315,"remaining_time":0}
+]}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/catboost_info/learn/events.out.tfevents b/stoneforge/tests/tests_ml/catboost_info/learn/events.out.tfevents
new file mode 100644
index 0000000..4fef598
Binary files /dev/null and b/stoneforge/tests/tests_ml/catboost_info/learn/events.out.tfevents differ
diff --git a/stoneforge/tests/tests_ml/catboost_info/learn_error.tsv b/stoneforge/tests/tests_ml/catboost_info/learn_error.tsv
new file mode 100644
index 0000000..62a7772
--- /dev/null
+++ b/stoneforge/tests/tests_ml/catboost_info/learn_error.tsv
@@ -0,0 +1,1001 @@
+iter	MultiClass
+0	1.160033152
+1	1.008673226
+2	0.8881235413
+3	0.7931164895
+4	0.7169791137
+5	0.6550197311
+6	0.6018018746
+7	0.5567899648
+8	0.5153413669
+9	0.4798684623
+10	0.4483862615
+11	0.4200210977
+12	0.3952006938
+13	0.3731886431
+14	0.355255603
+15	0.3388989025
+16	0.3228762737
+17	0.3078431732
+18	0.2950196968
+19	0.2846853653
+20	0.2749589302
+21	0.2646729384
+22	0.2563332737
+23	0.2471175927
+24	0.2384867018
+25	0.2300573612
+26	0.2233724229
+27	0.2169478296
+28	0.2119406638
+29	0.2057649098
+30	0.2000520492
+31	0.1965126723
+32	0.1923360381
+33	0.1892980359
+34	0.1850445532
+35	0.1812435958
+36	0.1779103494
+37	0.1740249347
+38	0.1712776147
+39	0.1676729645
+40	0.1646288984
+41	0.1618642346
+42	0.1594769872
+43	0.1573902236
+44	0.15443359
+45	0.1526542844
+46	0.1503569086
+47	0.1486240232
+48	0.1462510176
+49	0.1432071962
+50	0.1413126978
+51	0.1392605989
+52	0.1383447656
+53	0.1371648714
+54	0.1354617711
+55	0.1340781432
+56	0.1333193027
+57	0.1314188429
+58	0.1300198007
+59	0.129290178
+60	0.1281515222
+61	0.1266043786
+62	0.1244648859
+63	0.1229691976
+64	0.1217672114
+65	0.1210056657
+66	0.1200784689
+67	0.1195848609
+68	0.1184076767
+69	0.1173440878
+70	0.116348309
+71	0.1151051616
+72	0.1138342499
+73	0.1133271878
+74	0.1126772385
+75	0.1115231572
+76	0.1111092379
+77	0.1091238799
+78	0.1085269484
+79	0.1068956999
+80	0.1060582577
+81	0.1058287447
+82	0.1052144507
+83	0.1043389529
+84	0.1039158369
+85	0.1036174631
+86	0.1030097397
+87	0.1026335959
+88	0.1011456883
+89	0.1008214132
+90	0.1005665977
+91	0.09990963803
+92	0.09912540277
+93	0.09871654909
+94	0.09854409629
+95	0.09794063951
+96	0.09762818943
+97	0.0961057723
+98	0.09456927472
+99	0.09386985699
+100	0.09365653648
+101	0.09258156847
+102	0.09235329445
+103	0.0916293568
+104	0.0909260632
+105	0.09035906757
+106	0.08998253055
+107	0.08955201056
+108	0.08935522699
+109	0.08851084982
+110	0.08818847352
+111	0.08798163644
+112	0.08744401948
+113	0.08729597116
+114	0.08668279496
+115	0.08650571258
+116	0.0859538422
+117	0.08465541738
+118	0.0843635614
+119	0.08426636623
+120	0.08389444031
+121	0.08380993446
+122	0.08368598789
+123	0.08350338144
+124	0.0834080719
+125	0.08225333807
+126	0.08211161066
+127	0.08170022361
+128	0.08087975074
+129	0.08080126264
+130	0.07986984362
+131	0.0790369922
+132	0.0786015375
+133	0.07843459479
+134	0.07796580983
+135	0.07744102464
+136	0.07737915284
+137	0.07637387729
+138	0.07594220937
+139	0.07565616205
+140	0.0754761529
+141	0.0751585846
+142	0.07501106424
+143	0.07481101432
+144	0.07472715816
+145	0.07440649209
+146	0.07426382699
+147	0.074177802
+148	0.07357188104
+149	0.07267514898
+150	0.07193176512
+151	0.07179278459
+152	0.07155002292
+153	0.07147979815
+154	0.07095310979
+155	0.07051270925
+156	0.07022730581
+157	0.07005780821
+158	0.06936379257
+159	0.06892476281
+160	0.0684406685
+161	0.06836848449
+162	0.06822367076
+163	0.06816048776
+164	0.06755148157
+165	0.06718078867
+166	0.06690541031
+167	0.06664679935
+168	0.06651157824
+169	0.06635015477
+170	0.06606164018
+171	0.06595685035
+172	0.06584660415
+173	0.06534958652
+174	0.06527935503
+175	0.0650483267
+176	0.06495804209
+177	0.06490355729
+178	0.06475577269
+179	0.06413497121
+180	0.06403771018
+181	0.06364089812
+182	0.06360417958
+183	0.06355899668
+184	0.06340817821
+185	0.06278096686
+186	0.06269710609
+187	0.0626580215
+188	0.06230129103
+189	0.06222812109
+190	0.06171282392
+191	0.06121379032
+192	0.06112618332
+193	0.0610411749
+194	0.06096070427
+195	0.06085309209
+196	0.06077136056
+197	0.06074104592
+198	0.06070054562
+199	0.06045675478
+200	0.06028869204
+201	0.06012360119
+202	0.0600874122
+203	0.06005897814
+204	0.0600217828
+205	0.05997945438
+206	0.05994691106
+207	0.05960882317
+208	0.05930281564
+209	0.05912060249
+210	0.05887919966
+211	0.05859432326
+212	0.05815093818
+213	0.05811496324
+214	0.05806162906
+215	0.05755917018
+216	0.05751995596
+217	0.05721664162
+218	0.05708141984
+219	0.05694825463
+220	0.0564540281
+221	0.05626545471
+222	0.0559537747
+223	0.05591439256
+224	0.0556218581
+225	0.055201626
+226	0.05497188306
+227	0.05491863699
+228	0.0546869132
+229	0.05464517921
+230	0.05460520691
+231	0.0545601706
+232	0.0542878517
+233	0.05390079953
+234	0.05387868233
+235	0.05385980126
+236	0.05383206925
+237	0.05379781271
+238	0.05364039204
+239	0.05338457383
+240	0.05334149483
+241	0.05332399442
+242	0.05327959471
+243	0.05307932416
+244	0.05289261602
+245	0.05286431079
+246	0.05267764482
+247	0.05257629843
+248	0.05232647038
+249	0.05230154063
+250	0.05225685233
+251	0.05211971243
+252	0.05209966226
+253	0.05205208554
+254	0.05197528718
+255	0.05163197932
+256	0.05160297843
+257	0.05155568381
+258	0.05149230371
+259	0.0513888121
+260	0.05136931083
+261	0.0510104664
+262	0.05099115208
+263	0.05094886452
+264	0.05091750418
+265	0.05070296675
+266	0.05067001411
+267	0.05058679132
+268	0.05056392918
+269	0.05054119534
+270	0.05024795987
+271	0.05023367555
+272	0.04985783531
+273	0.04983536449
+274	0.04959688184
+275	0.04942496289
+276	0.04940252204
+277	0.04910836123
+278	0.0489273979
+279	0.04855702539
+280	0.04846045331
+281	0.04842280525
+282	0.04832033878
+283	0.04829444022
+284	0.04826563825
+285	0.04797336458
+286	0.04776590546
+287	0.04750622704
+288	0.04740055322
+289	0.04735226902
+290	0.04714561977
+291	0.04712487644
+292	0.04709006259
+293	0.04699735783
+294	0.04697710322
+295	0.04684743755
+296	0.0468095009
+297	0.04679805734
+298	0.04677093189
+299	0.04670214526
+300	0.04669014568
+301	0.04660665683
+302	0.04659342111
+303	0.04654444481
+304	0.04652279356
+305	0.0462779216
+306	0.04618517719
+307	0.04617104011
+308	0.04613505786
+309	0.04603009761
+310	0.045925653
+311	0.04590150654
+312	0.04588582067
+313	0.04582769457
+314	0.04581691864
+315	0.04549492839
+316	0.04519770776
+317	0.0451400209
+318	0.04505667641
+319	0.0450057904
+320	0.0449427691
+321	0.04486577277
+322	0.04457760413
+323	0.04450235461
+324	0.04425032736
+325	0.04404845427
+326	0.04403499328
+327	0.04399852055
+328	0.04395914338
+329	0.04381322626
+330	0.04369537893
+331	0.04368498071
+332	0.04366617149
+333	0.04365319924
+334	0.04362900955
+335	0.04361270042
+336	0.04360066891
+337	0.04341491548
+338	0.04340320547
+339	0.04339460433
+340	0.04336997843
+341	0.04329545696
+342	0.04326067858
+343	0.043251725
+344	0.04310192278
+345	0.04302347742
+346	0.04290261525
+347	0.04279411047
+348	0.0427689654
+349	0.04275516652
+350	0.0427383065
+351	0.04264768964
+352	0.04263274798
+353	0.04261823376
+354	0.04235116715
+355	0.0423248028
+356	0.04224058018
+357	0.04220636345
+358	0.0421009732
+359	0.0418636344
+360	0.04184384326
+361	0.04179635822
+362	0.0417605827
+363	0.04158459246
+364	0.04152619311
+365	0.04149521981
+366	0.0414700846
+367	0.04143564518
+368	0.04142648302
+369	0.04141572671
+370	0.04123739104
+371	0.04122441316
+372	0.04100765097
+373	0.04092182214
+374	0.04091235533
+375	0.04088646718
+376	0.04086748565
+377	0.04074819336
+378	0.04073436745
+379	0.04067744945
+380	0.04055765473
+381	0.04044099743
+382	0.04035737197
+383	0.04031457422
+384	0.04028701475
+385	0.04027829299
+386	0.04025611345
+387	0.04020513905
+388	0.04018833309
+389	0.04017483009
+390	0.04012913099
+391	0.03990729664
+392	0.03986318057
+393	0.03979806117
+394	0.03978209855
+395	0.0395206444
+396	0.03939167005
+397	0.03936557393
+398	0.03931827208
+399	0.03913576714
+400	0.03911795541
+401	0.03908934809
+402	0.03904693822
+403	0.03902893089
+404	0.03901413031
+405	0.03882856931
+406	0.03872483743
+407	0.03863167684
+408	0.0386171227
+409	0.03853694945
+410	0.03843725339
+411	0.03838455136
+412	0.0381644459
+413	0.03801408053
+414	0.03798923372
+415	0.03790103928
+416	0.03786993306
+417	0.03782021637
+418	0.03766285397
+419	0.03755764554
+420	0.03754274721
+421	0.03734306282
+422	0.03728477824
+423	0.03721575043
+424	0.03714255782
+425	0.03713252364
+426	0.03710962457
+427	0.03708823304
+428	0.03702499593
+429	0.03698715631
+430	0.03690941265
+431	0.0368940519
+432	0.0368827281
+433	0.03686017589
+434	0.03683215817
+435	0.03681344065
+436	0.03677739241
+437	0.03672050285
+438	0.03668995921
+439	0.03668093144
+440	0.03666033061
+441	0.03664108247
+442	0.03663428851
+443	0.03660461632
+444	0.03651605123
+445	0.03649295577
+446	0.03647505553
+447	0.036463431
+448	0.03642268876
+449	0.03630821851
+450	0.03630113441
+451	0.03622212121
+452	0.03610920182
+453	0.03609758381
+454	0.03606740268
+455	0.03599516587
+456	0.03582319582
+457	0.0358146809
+458	0.03578706065
+459	0.03575268608
+460	0.03574386428
+461	0.03569364704
+462	0.03568063436
+463	0.0356598993
+464	0.03564854951
+465	0.03551634925
+466	0.03549420393
+467	0.03547956297
+468	0.03544556623
+469	0.03543406687
+470	0.0353842035
+471	0.03531320695
+472	0.03530502567
+473	0.03527230915
+474	0.0352264688
+475	0.03520414522
+476	0.03509263104
+477	0.03508414695
+478	0.03507026336
+479	0.03491132216
+480	0.03490467698
+481	0.03487591791
+482	0.03485937578
+483	0.0348484559
+484	0.03472358165
+485	0.03460984075
+486	0.0345972085
+487	0.03457688509
+488	0.03450145145
+489	0.03444675883
+490	0.03438159948
+491	0.03435074164
+492	0.03431876669
+493	0.03429137404
+494	0.03427214258
+495	0.03423312763
+496	0.03421503366
+497	0.03420128703
+498	0.03406542147
+499	0.03390318958
+500	0.03389378103
+501	0.03387579278
+502	0.03379886281
+503	0.0337743283
+504	0.03376697859
+505	0.03375738076
+506	0.03372691183
+507	0.03370408455
+508	0.03359087209
+509	0.03355356579
+510	0.03348260778
+511	0.03338689268
+512	0.03337436405
+513	0.0333263933
+514	0.03330845823
+515	0.03329755619
+516	0.03329034672
+517	0.03328305708
+518	0.03327622683
+519	0.0332676599
+520	0.03325394782
+521	0.03324567136
+522	0.03323089745
+523	0.03322107743
+524	0.03316435537
+525	0.03315277754
+526	0.03314619233
+527	0.03310415794
+528	0.03308940035
+529	0.03299316546
+530	0.03290758896
+531	0.03289649204
+532	0.03289079862
+533	0.03284169565
+534	0.03281122611
+535	0.0328030323
+536	0.0327064234
+537	0.03261310302
+538	0.03259689203
+539	0.03258947864
+540	0.03258382506
+541	0.03255166189
+542	0.03253121396
+543	0.03239707126
+544	0.03233488348
+545	0.03225954025
+546	0.03215917022
+547	0.03215066587
+548	0.03213930065
+549	0.03212068017
+550	0.03209629524
+551	0.03205774208
+552	0.03203691266
+553	0.03201495359
+554	0.03193871108
+555	0.03190968832
+556	0.03189641061
+557	0.03189214839
+558	0.03188091475
+559	0.03182915248
+560	0.03181253278
+561	0.03176195694
+562	0.0316978627
+563	0.03163917423
+564	0.0315622924
+565	0.03149615746
+566	0.03147964054
+567	0.03144101216
+568	0.03143160056
+569	0.03142022449
+570	0.03139719018
+571	0.03135256171
+572	0.03129453851
+573	0.03127246926
+574	0.03124860896
+575	0.03119037052
+576	0.0311592702
+577	0.03115136367
+578	0.0311266516
+579	0.03112205614
+580	0.03111395406
+581	0.0311006962
+582	0.03109471388
+583	0.03107083379
+584	0.03097675709
+585	0.03096600229
+586	0.03096158133
+587	0.03094960337
+588	0.03094087644
+589	0.03092797226
+590	0.03091757006
+591	0.03086376385
+592	0.03082948064
+593	0.03077946147
+594	0.0307674574
+595	0.03075791442
+596	0.03075372426
+597	0.03070617726
+598	0.03068149877
+599	0.03067323112
+600	0.03066662529
+601	0.03066212123
+602	0.03065665474
+603	0.03065108794
+604	0.03054826119
+605	0.03052656921
+606	0.03043035026
+607	0.03040204751
+608	0.03038464911
+609	0.03031150772
+610	0.03028674661
+611	0.03024984829
+612	0.03017124724
+613	0.03014600324
+614	0.03013761028
+615	0.03012744285
+616	0.03010411839
+617	0.03008834154
+618	0.03003369623
+619	0.03002495102
+620	0.02996858568
+621	0.02996409988
+622	0.02994894962
+623	0.02993696216
+624	0.02992612967
+625	0.02984927443
+626	0.02979581469
+627	0.02976539254
+628	0.02971011729
+629	0.02962423052
+630	0.02960036713
+631	0.02958940149
+632	0.02957588507
+633	0.02951609243
+634	0.02950680693
+635	0.02948151137
+636	0.02947629207
+637	0.02942817314
+638	0.02941439677
+639	0.0293823908
+640	0.02937342382
+641	0.02936380125
+642	0.02935584495
+643	0.02932434288
+644	0.029320235
+645	0.02931039971
+646	0.02930282704
+647	0.02927863687
+648	0.02927081487
+649	0.02925649888
+650	0.02921421558
+651	0.02915158475
+652	0.02914654608
+653	0.02913281664
+654	0.02912856535
+655	0.02911910739
+656	0.02909215104
+657	0.02907713449
+658	0.02903953506
+659	0.0290306791
+660	0.02900995673
+661	0.02898829763
+662	0.02897764142
+663	0.02896859616
+664	0.02891620509
+665	0.02888715857
+666	0.02887788998
+667	0.02886161088
+668	0.02883236057
+669	0.0288141427
+670	0.02881056941
+671	0.02878278527
+672	0.02877417387
+673	0.02872215364
+674	0.02870768294
+675	0.02869909677
+676	0.02868066708
+677	0.02859642625
+678	0.02858811474
+679	0.02857385585
+680	0.0285283975
+681	0.02851158389
+682	0.02849337391
+683	0.02846595106
+684	0.028456776
+685	0.02842819638
+686	0.02842323692
+687	0.02841313969
+688	0.02840326324
+689	0.02833955018
+690	0.02832629289
+691	0.02828993795
+692	0.02828577645
+693	0.02827501951
+694	0.02826778187
+695	0.02823814298
+696	0.0282299856
+697	0.02822046234
+698	0.02821535659
+699	0.0282085824
+700	0.02820022063
+701	0.0281952966
+702	0.02815534324
+703	0.02815162679
+704	0.02811759191
+705	0.02801055464
+706	0.02798581971
+707	0.02797382773
+708	0.02794370389
+709	0.02793705349
+710	0.02793237697
+711	0.02792762848
+712	0.02791303954
+713	0.02785980061
+714	0.02779280862
+715	0.02775204778
+716	0.02772187542
+717	0.02763956462
+718	0.02760563202
+719	0.02758605921
+720	0.02757958131
+721	0.02754817283
+722	0.02745633667
+723	0.02744621287
+724	0.02743602837
+725	0.027426361
+726	0.02741889055
+727	0.02741198924
+728	0.02738993344
+729	0.02728424825
+730	0.02728125614
+731	0.02725893063
+732	0.02723869636
+733	0.02716161257
+734	0.02713828064
+735	0.02713171714
+736	0.02711962197
+737	0.02711462755
+738	0.02706637228
+739	0.02699547895
+740	0.02699189104
+741	0.02695623953
+742	0.02694306696
+743	0.0269246898
+744	0.02691441808
+745	0.02687652898
+746	0.02685505766
+747	0.02684906965
+748	0.02682367574
+749	0.02681755825
+750	0.02680065202
+751	0.02678964429
+752	0.0267367592
+753	0.02669856172
+754	0.02669144291
+755	0.02668775657
+756	0.02668440948
+757	0.02659284947
+758	0.02657445689
+759	0.02656470179
+760	0.02653963194
+761	0.02653270889
+762	0.02650442012
+763	0.02645699797
+764	0.02636849252
+765	0.02636469683
+766	0.02635664192
+767	0.02632323718
+768	0.02631477653
+769	0.02628811693
+770	0.02626957332
+771	0.0262651055
+772	0.02625774839
+773	0.02624689512
+774	0.02619720299
+775	0.0261870716
+776	0.02618333886
+777	0.02614901722
+778	0.02613471676
+779	0.02611262808
+780	0.02611046878
+781	0.02609893965
+782	0.02607244396
+783	0.02602443608
+784	0.02600695947
+785	0.02599514107
+786	0.02597510569
+787	0.02594647083
+788	0.02594195753
+789	0.02591110424
+790	0.02586411329
+791	0.02583741607
+792	0.02581581331
+793	0.02580876397
+794	0.02579990459
+795	0.02570221924
+796	0.02567624045
+797	0.02565669234
+798	0.02565196031
+799	0.02564126793
+800	0.02562263526
+801	0.02561330565
+802	0.02560338215
+803	0.0255991496
+804	0.02559316325
+805	0.02558136803
+806	0.02557230731
+807	0.02556862501
+808	0.02549890541
+809	0.02549189489
+810	0.02548783973
+811	0.02546882203
+812	0.02544718682
+813	0.02544185907
+814	0.02543005094
+815	0.02542619235
+816	0.02541820789
+817	0.0254127645
+818	0.02540116476
+819	0.02538324342
+820	0.02535526742
+821	0.02531657161
+822	0.02531080769
+823	0.02530550836
+824	0.0252958085
+825	0.02528371888
+826	0.02526385979
+827	0.02524302459
+828	0.02523333086
+829	0.02522294582
+830	0.02519052206
+831	0.02518401644
+832	0.02515756447
+833	0.02515410283
+834	0.02513777417
+835	0.02513110809
+836	0.02512389493
+837	0.0251111454
+838	0.02508678731
+839	0.02508231731
+840	0.02506235829
+841	0.0250580117
+842	0.02502469503
+843	0.0250083634
+844	0.02499158274
+845	0.02495413124
+846	0.024944665
+847	0.02491248278
+848	0.02489625508
+849	0.02486796749
+850	0.02486130916
+851	0.0248507132
+852	0.02480442923
+853	0.02478168926
+854	0.02477237341
+855	0.0247653735
+856	0.02476165804
+857	0.02474681606
+858	0.0247392133
+859	0.0247334647
+860	0.02472781995
+861	0.02472404596
+862	0.02471132637
+863	0.02470461834
+864	0.02466474784
+865	0.02463549014
+866	0.02459751632
+867	0.02456658494
+868	0.0245349431
+869	0.02453181104
+870	0.02452710158
+871	0.02451645205
+872	0.02448830075
+873	0.02447869069
+874	0.02446320843
+875	0.02445766002
+876	0.02444557097
+877	0.02440709318
+878	0.02439801428
+879	0.02439102947
+880	0.02438700937
+881	0.0243830278
+882	0.02437976675
+883	0.02436996739
+884	0.0243662823
+885	0.02436277412
+886	0.02434522499
+887	0.0243318236
+888	0.02429761963
+889	0.02429392789
+890	0.02428605805
+891	0.02427827978
+892	0.02425750782
+893	0.02425173856
+894	0.02424258499
+895	0.02420970418
+896	0.02420415676
+897	0.02418282221
+898	0.02415830608
+899	0.02413690952
+900	0.02405252518
+901	0.02403662952
+902	0.02402495753
+903	0.02401868732
+904	0.02401365048
+905	0.02401053154
+906	0.0240077297
+907	0.02397283153
+908	0.02395709503
+909	0.02390952947
+910	0.02390072237
+911	0.02389324751
+912	0.02388711252
+913	0.02388240358
+914	0.02383856501
+915	0.02380399295
+916	0.02379818277
+917	0.02379369427
+918	0.0237862419
+919	0.02377702495
+920	0.02377412791
+921	0.02376901607
+922	0.02376484466
+923	0.02374952939
+924	0.02373117357
+925	0.02372463527
+926	0.02366769968
+927	0.02366379669
+928	0.02364036456
+929	0.02362875696
+930	0.02361197317
+931	0.02360711158
+932	0.02358730033
+933	0.02357156117
+934	0.02356127163
+935	0.02354210757
+936	0.02352752711
+937	0.02351458274
+938	0.02349428298
+939	0.02347219413
+940	0.02345135964
+941	0.02342243826
+942	0.02340197366
+943	0.0233883498
+944	0.02337676598
+945	0.02335305171
+946	0.02334969302
+947	0.02333328615
+948	0.02331343611
+949	0.02330509052
+950	0.02329027449
+951	0.02327422111
+952	0.02326776933
+953	0.02325271865
+954	0.02324576803
+955	0.02323700398
+956	0.02318588118
+957	0.02317308766
+958	0.02316545401
+959	0.02314997662
+960	0.02314249514
+961	0.02313902133
+962	0.02313148571
+963	0.02309615497
+964	0.02308552725
+965	0.02306858804
+966	0.02300349215
+967	0.0229939654
+968	0.02297702085
+969	0.02296994833
+970	0.02296436766
+971	0.02296025073
+972	0.0229512616
+973	0.02293930675
+974	0.02291980757
+975	0.02291633192
+976	0.02290005426
+977	0.02289727501
+978	0.02287880829
+979	0.02285149379
+980	0.02284379327
+981	0.02283966579
+982	0.02283217514
+983	0.02281227017
+984	0.02278541809
+985	0.02277400324
+986	0.02276918683
+987	0.02276296819
+988	0.02274521284
+989	0.02272135264
+990	0.02271125485
+991	0.02270433257
+992	0.02269727004
+993	0.02268913566
+994	0.02267941527
+995	0.02266977305
+996	0.02266067452
+997	0.02264972592
+998	0.02264699173
+999	0.02264030443
diff --git a/stoneforge/tests/tests_ml/catboost_info/time_left.tsv b/stoneforge/tests/tests_ml/catboost_info/time_left.tsv
new file mode 100644
index 0000000..d7420ae
--- /dev/null
+++ b/stoneforge/tests/tests_ml/catboost_info/time_left.tsv
@@ -0,0 +1,1001 @@
+iter	Passed	Remaining
+0	162	162350
+1	171	85694
+2	178	59478
+3	186	46427
+4	194	38646
+5	202	33551
+6	209	29787
+7	216	26906
+8	224	24732
+9	231	22957
+10	238	21481
+11	246	20272
+12	253	19231
+13	260	18333
+14	267	17535
+15	274	16852
+16	281	16251
+17	288	15731
+18	295	15276
+19	302	14822
+20	309	14420
+21	316	14052
+22	323	13729
+23	330	13442
+24	338	13187
+25	345	12943
+26	353	12722
+27	360	12513
+28	367	12299
+29	375	12130
+30	383	11975
+31	390	11810
+32	397	11661
+33	404	11503
+34	412	11360
+35	418	11210
+36	425	11075
+37	433	10969
+38	440	10863
+39	447	10742
+40	454	10640
+41	462	10544
+42	469	10440
+43	476	10343
+44	483	10252
+45	489	10158
+46	496	10063
+47	503	9983
+48	509	9895
+49	516	9822
+50	523	9741
+51	529	9659
+52	536	9586
+53	543	9513
+54	549	9446
+55	556	9386
+56	563	9315
+57	570	9259
+58	577	9204
+59	583	9145
+60	590	9089
+61	596	9030
+62	605	9000
+63	612	8952
+64	618	8898
+65	624	8840
+66	631	8795
+67	637	8741
+68	644	8696
+69	651	8659
+70	658	8619
+71	665	8578
+72	672	8545
+73	679	8503
+74	686	8461
+75	692	8424
+76	699	8383
+77	706	8356
+78	713	8317
+79	721	8294
+80	728	8261
+81	735	8229
+82	742	8200
+83	749	8171
+84	756	8140
+85	762	8107
+86	770	8082
+87	777	8057
+88	785	8041
+89	792	8010
+90	799	7981
+91	805	7948
+92	812	7923
+93	819	7893
+94	825	7862
+95	832	7839
+96	839	7812
+97	846	7793
+98	854	7773
+99	861	7749
+100	867	7721
+101	874	7700
+102	880	7670
+103	887	7645
+104	894	7624
+105	901	7604
+106	908	7578
+107	914	7556
+108	921	7529
+109	928	7513
+110	935	7488
+111	941	7467
+112	949	7451
+113	955	7428
+114	962	7410
+115	969	7390
+116	977	7373
+117	984	7358
+118	990	7334
+119	998	7318
+120	1004	7296
+121	1010	7271
+122	1016	7248
+123	1022	7225
+124	1029	7208
+125	1037	7194
+126	1043	7172
+127	1050	7158
+128	1058	7144
+129	1065	7128
+130	1072	7116
+131	1080	7102
+132	1086	7080
+133	1092	7061
+134	1100	7049
+135	1107	7035
+136	1114	7021
+137	1122	7009
+138	1129	6995
+139	1136	6980
+140	1143	6964
+141	1149	6946
+142	1156	6930
+143	1163	6916
+144	1169	6894
+145	1175	6877
+146	1181	6857
+147	1188	6839
+148	1195	6827
+149	1202	6813
+150	1210	6804
+151	1216	6785
+152	1223	6773
+153	1230	6757
+154	1237	6743
+155	1244	6730
+156	1251	6717
+157	1257	6703
+158	1264	6690
+159	1272	6681
+160	1280	6670
+161	1286	6654
+162	1293	6642
+163	1299	6625
+164	1306	6613
+165	1314	6603
+166	1321	6590
+167	1328	6580
+168	1335	6565
+169	1342	6552
+170	1349	6540
+171	1355	6526
+172	1362	6515
+173	1370	6503
+174	1376	6490
+175	1383	6477
+176	1390	6463
+177	1396	6448
+178	1403	6435
+179	1410	6424
+180	1417	6415
+181	1425	6405
+182	1432	6393
+183	1438	6378
+184	1444	6364
+185	1451	6352
+186	1458	6341
+187	1465	6328
+188	1472	6318
+189	1479	6306
+190	1486	6294
+191	1493	6284
+192	1499	6271
+193	1507	6261
+194	1514	6250
+195	1520	6239
+196	1527	6225
+197	1533	6210
+198	1540	6198
+199	1546	6185
+200	1552	6172
+201	1559	6162
+202	1566	6148
+203	1572	6136
+204	1578	6122
+205	1585	6110
+206	1591	6097
+207	1598	6087
+208	1606	6078
+209	1613	6068
+210	1620	6058
+211	1627	6048
+212	1634	6038
+213	1640	6025
+214	1647	6014
+215	1654	6005
+216	1661	5994
+217	1668	5985
+218	1675	5975
+219	1682	5963
+220	1689	5956
+221	1696	5946
+222	1704	5939
+223	1711	5927
+224	1717	5917
+225	1725	5909
+226	1732	5898
+227	1738	5886
+228	1745	5876
+229	1752	5866
+230	1758	5853
+231	1764	5842
+232	1772	5834
+233	1780	5827
+234	1787	5817
+235	1793	5806
+236	1800	5797
+237	1807	5787
+238	1814	5776
+239	1821	5767
+240	1827	5755
+241	1834	5745
+242	1840	5734
+243	1847	5723
+244	1854	5714
+245	1860	5703
+246	1868	5695
+247	1875	5686
+248	1882	5678
+249	1889	5667
+250	1895	5656
+251	1902	5647
+252	1908	5636
+253	1915	5625
+254	1922	5616
+255	1929	5607
+256	1936	5599
+257	1943	5588
+258	1964	5619
+259	1970	5609
+260	1976	5597
+261	1984	5589
+262	1990	5578
+263	1997	5567
+264	2003	5557
+265	2010	5546
+266	2016	5537
+267	2023	5525
+268	2030	5516
+269	2036	5506
+270	2043	5497
+271	2051	5489
+272	2058	5481
+273	2064	5470
+274	2072	5462
+275	2079	5453
+276	2085	5443
+277	2093	5435
+278	2100	5429
+279	2108	5420
+280	2115	5413
+281	2122	5403
+282	2129	5395
+283	2135	5384
+284	2141	5373
+285	2149	5366
+286	2156	5358
+287	2164	5350
+288	2171	5341
+289	2178	5332
+290	2185	5324
+291	2192	5315
+292	2199	5306
+293	2205	5296
+294	2212	5287
+295	2219	5278
+296	2225	5268
+297	2232	5258
+298	2238	5247
+299	2245	5239
+300	2251	5228
+301	2257	5218
+302	2264	5210
+303	2271	5201
+304	2278	5193
+305	2286	5185
+306	2294	5178
+307	2300	5169
+308	2307	5160
+309	2314	5152
+310	2321	5143
+311	2328	5133
+312	2334	5123
+313	2340	5113
+314	2346	5103
+315	2353	5094
+316	2361	5087
+317	2368	5078
+318	2375	5071
+319	2382	5062
+320	2388	5053
+321	2396	5044
+322	2403	5037
+323	2410	5029
+324	2417	5021
+325	2425	5013
+326	2432	5006
+327	2438	4995
+328	2445	4986
+329	2451	4977
+330	2458	4968
+331	2464	4958
+332	2471	4949
+333	2477	4940
+334	2484	4932
+335	2491	4924
+336	2498	4916
+337	2506	4909
+338	2513	4900
+339	2519	4890
+340	2526	4881
+341	2533	4873
+342	2539	4864
+343	2546	4855
+344	2552	4846
+345	2559	4838
+346	2566	4829
+347	2573	4820
+348	2579	4811
+349	2585	4801
+350	2592	4793
+351	2599	4785
+352	2606	4776
+353	2612	4767
+354	2620	4760
+355	2627	4753
+356	2635	4746
+357	2642	4738
+358	2649	4730
+359	2656	4723
+360	2664	4716
+361	2671	4708
+362	2678	4699
+363	2685	4692
+364	2692	4684
+365	2699	4675
+366	2706	4667
+367	2713	4659
+368	2719	4650
+369	2726	4642
+370	2733	4635
+371	2740	4626
+372	2748	4619
+373	2755	4611
+374	2761	4603
+375	2767	4593
+376	2774	4584
+377	2781	4577
+378	2788	4568
+379	2796	4562
+380	2804	4555
+381	2810	4547
+382	2817	4538
+383	2824	4530
+384	2830	4520
+385	2836	4511
+386	2843	4504
+387	2850	4495
+388	2856	4486
+389	2863	4478
+390	2869	4469
+391	2877	4462
+392	2883	4454
+393	2891	4446
+394	2897	4437
+395	2904	4430
+396	2912	4423
+397	2919	4416
+398	2927	4409
+399	2934	4401
+400	2941	4393
+401	2947	4384
+402	2954	4376
+403	2960	4367
+404	2966	4358
+405	2974	4351
+406	2981	4343
+407	2988	4336
+408	2994	4327
+409	3001	4319
+410	3008	4311
+411	3015	4304
+412	3023	4297
+413	3030	4289
+414	3037	4281
+415	3044	4273
+416	3051	4266
+417	3057	4257
+418	3065	4250
+419	3077	4250
+420	3085	4242
+421	3092	4235
+422	3099	4227
+423	3105	4219
+424	3112	4211
+425	3119	4203
+426	3126	4195
+427	3133	4187
+428	3140	4180
+429	3147	4172
+430	3154	4164
+431	3161	4157
+432	3168	4149
+433	3174	4140
+434	3181	4132
+435	3188	4125
+436	3195	4116
+437	3202	4108
+438	3208	4100
+439	3215	4092
+440	3222	4084
+441	3228	4076
+442	3235	4068
+443	3242	4059
+444	3249	4052
+445	3256	4045
+446	3263	4037
+447	3270	4029
+448	3276	4021
+449	3284	4013
+450	3290	4006
+451	3298	3999
+452	3305	3991
+453	3312	3984
+454	3319	3975
+455	3326	3968
+456	3334	3961
+457	3340	3953
+458	3347	3945
+459	3354	3938
+460	3361	3930
+461	3367	3921
+462	3374	3914
+463	3381	3906
+464	3388	3898
+465	3396	3891
+466	3403	3884
+467	3410	3877
+468	3417	3869
+469	3424	3861
+470	3430	3853
+471	3437	3845
+472	3443	3837
+473	3450	3829
+474	3457	3821
+475	3465	3814
+476	3471	3806
+477	3479	3799
+478	3485	3791
+479	3492	3783
+480	3499	3775
+481	3505	3766
+482	3511	3758
+483	3518	3751
+484	3525	3743
+485	3532	3736
+486	3539	3728
+487	3546	3720
+488	3552	3712
+489	3560	3705
+490	3567	3698
+491	3574	3690
+492	3582	3683
+493	3588	3676
+494	3595	3668
+495	3602	3661
+496	3609	3653
+497	3617	3646
+498	3624	3638
+499	3631	3631
+500	3638	3623
+501	3645	3616
+502	3651	3608
+503	3658	3600
+504	3665	3592
+505	3672	3585
+506	3679	3577
+507	3685	3569
+508	3693	3562
+509	3700	3554
+510	3707	3548
+511	3714	3540
+512	3721	3532
+513	3729	3526
+514	3736	3518
+515	3742	3510
+516	3749	3502
+517	3756	3495
+518	3762	3487
+519	3769	3479
+520	3776	3472
+521	3783	3464
+522	3790	3456
+523	3797	3449
+524	3805	3442
+525	3811	3435
+526	3818	3427
+527	3825	3419
+528	3832	3412
+529	3839	3405
+530	3846	3397
+531	3853	3390
+532	3860	3382
+533	3867	3375
+534	3874	3367
+535	3881	3359
+536	3888	3352
+537	3896	3345
+538	3902	3337
+539	3909	3330
+540	3916	3322
+541	3923	3315
+542	3930	3307
+543	3937	3300
+544	3945	3293
+545	3951	3286
+546	3959	3278
+547	3965	3270
+548	3971	3262
+549	3978	3255
+550	3985	3247
+551	3993	3240
+552	3999	3232
+553	4007	3226
+554	4015	3219
+555	4022	3212
+556	4029	3204
+557	4036	3197
+558	4042	3189
+559	4049	3181
+560	4056	3174
+561	4063	3167
+562	4071	3160
+563	4078	3152
+564	4085	3145
+565	4092	3137
+566	4099	3130
+567	4105	3122
+568	4113	3115
+569	4120	3108
+570	4127	3101
+571	4134	3093
+572	4142	3086
+573	4149	3079
+574	4156	3072
+575	4163	3064
+576	4170	3057
+577	4176	3049
+578	4183	3041
+579	4190	3034
+580	4196	3026
+581	4203	3019
+582	4209	3010
+583	4216	3003
+584	4223	2996
+585	4229	2988
+586	4236	2980
+587	4242	2972
+588	4249	2965
+589	4256	2957
+590	4262	2949
+591	4269	2942
+592	4276	2934
+593	4282	2927
+594	4289	2920
+595	4296	2912
+596	4303	2904
+597	4309	2897
+598	4316	2889
+599	4323	2882
+600	4331	2875
+601	4337	2867
+602	4344	2860
+603	4352	2853
+604	4359	2846
+605	4366	2838
+606	4373	2831
+607	4381	2824
+608	4388	2817
+609	4395	2810
+610	4402	2803
+611	4409	2795
+612	4417	2788
+613	4423	2781
+614	4430	2773
+615	4437	2765
+616	4444	2758
+617	4451	2751
+618	4458	2744
+619	4464	2736
+620	4471	2729
+621	4478	2721
+622	4485	2714
+623	4492	2706
+624	4498	2699
+625	4505	2691
+626	4512	2684
+627	4519	2677
+628	4526	2669
+629	4533	2662
+630	4540	2654
+631	4546	2647
+632	4553	2640
+633	4561	2633
+634	4567	2625
+635	4573	2617
+636	4580	2610
+637	4587	2603
+638	4593	2595
+639	4600	2588
+640	4607	2580
+641	4614	2573
+642	4621	2566
+643	4628	2558
+644	4635	2551
+645	4642	2543
+646	4648	2536
+647	4655	2529
+648	4662	2521
+649	4668	2514
+650	4676	2506
+651	4683	2499
+652	4690	2492
+653	4697	2484
+654	4703	2477
+655	4709	2469
+656	4716	2462
+657	4723	2454
+658	4730	2447
+659	4736	2440
+660	4743	2432
+661	4750	2425
+662	4757	2418
+663	4764	2410
+664	4771	2403
+665	4778	2396
+666	4785	2388
+667	4792	2381
+668	4799	2374
+669	4805	2366
+670	4813	2359
+671	4819	2352
+672	4826	2345
+673	4834	2338
+674	4840	2330
+675	4847	2323
+676	4853	2315
+677	4861	2308
+678	4867	2301
+679	4873	2293
+680	4880	2286
+681	4888	2279
+682	4895	2272
+683	4902	2265
+684	4909	2257
+685	4916	2250
+686	4923	2242
+687	4929	2235
+688	4936	2228
+689	4943	2221
+690	4950	2213
+691	4957	2206
+692	4965	2199
+693	4971	2192
+694	4977	2184
+695	4984	2177
+696	4991	2169
+697	4998	2162
+698	5005	2155
+699	5012	2148
+700	5018	2140
+701	5025	2133
+702	5032	2126
+703	5039	2118
+704	5046	2111
+705	5053	2104
+706	5062	2097
+707	5068	2090
+708	5075	2083
+709	5081	2075
+710	5088	2068
+711	5094	2060
+712	5101	2053
+713	5108	2046
+714	5115	2039
+715	5123	2032
+716	5129	2024
+717	5137	2017
+718	5144	2010
+719	5151	2003
+720	5158	1996
+721	5165	1989
+722	5173	1982
+723	5180	1974
+724	5187	1967
+725	5194	1960
+726	5201	1953
+727	5208	1946
+728	5216	1939
+729	5223	1931
+730	5229	1924
+731	5236	1917
+732	5243	1909
+733	5250	1902
+734	5257	1895
+735	5263	1888
+736	5270	1880
+737	5278	1873
+738	5285	1866
+739	5292	1859
+740	5298	1852
+741	5305	1844
+742	5312	1837
+743	5320	1830
+744	5326	1823
+745	5333	1816
+746	5341	1809
+747	5347	1801
+748	5354	1794
+749	5362	1787
+750	5369	1780
+751	5376	1773
+752	5383	1766
+753	5391	1758
+754	5398	1751
+755	5405	1744
+756	5411	1737
+757	5419	1730
+758	5425	1722
+759	5432	1715
+760	5439	1708
+761	5445	1700
+762	5453	1693
+763	5459	1686
+764	5467	1679
+765	5473	1672
+766	5480	1664
+767	5487	1657
+768	5493	1650
+769	5500	1643
+770	5507	1635
+771	5514	1628
+772	5521	1621
+773	5527	1613
+774	5534	1606
+775	5541	1599
+776	5548	1592
+777	5555	1585
+778	5562	1577
+779	5568	1570
+780	5575	1563
+781	5582	1556
+782	5589	1549
+783	5597	1542
+784	5604	1534
+785	5611	1527
+786	5618	1520
+787	5624	1513
+788	5630	1505
+789	5638	1498
+790	5645	1491
+791	5652	1484
+792	5659	1477
+793	5666	1470
+794	5673	1462
+795	5680	1455
+796	5686	1448
+797	5694	1441
+798	5700	1434
+799	5707	1426
+800	5714	1419
+801	5721	1412
+802	5727	1405
+803	5734	1397
+804	5740	1390
+805	5747	1383
+806	5753	1376
+807	5760	1368
+808	5768	1361
+809	5775	1354
+810	5782	1347
+811	5789	1340
+812	5796	1333
+813	5803	1326
+814	5810	1318
+815	5817	1311
+816	5824	1304
+817	5831	1297
+818	5837	1290
+819	5843	1282
+820	5851	1275
+821	5858	1268
+822	5865	1261
+823	5872	1254
+824	5879	1247
+825	5886	1240
+826	5893	1232
+827	5900	1225
+828	5907	1218
+829	5914	1211
+830	5921	1204
+831	5928	1197
+832	5936	1190
+833	5943	1182
+834	5950	1175
+835	5956	1168
+836	5963	1161
+837	5969	1154
+838	5976	1146
+839	5983	1139
+840	5990	1132
+841	5997	1125
+842	6004	1118
+843	6011	1111
+844	6018	1103
+845	6025	1096
+846	6032	1089
+847	6038	1082
+848	6045	1075
+849	6052	1068
+850	6059	1060
+851	6066	1053
+852	6073	1046
+853	6079	1039
+854	6086	1032
+855	6094	1025
+856	6100	1017
+857	6108	1010
+858	6115	1003
+859	6122	996
+860	6129	989
+861	6135	982
+862	6143	975
+863	6149	967
+864	6156	960
+865	6163	953
+866	6170	946
+867	6178	939
+868	6184	932
+869	6192	925
+870	6199	918
+871	6206	911
+872	6213	903
+873	6219	896
+874	6226	889
+875	6233	882
+876	6239	875
+877	6246	868
+878	6253	860
+879	6260	853
+880	6266	846
+881	6273	839
+882	6279	832
+883	6286	824
+884	6293	817
+885	6299	810
+886	6305	803
+887	6312	796
+888	6320	789
+889	6327	782
+890	6334	774
+891	6341	767
+892	6348	760
+893	6355	753
+894	6362	746
+895	6369	739
+896	6376	732
+897	6384	725
+898	6392	718
+899	6399	711
+900	6406	703
+901	6413	696
+902	6420	689
+903	6427	682
+904	6433	675
+905	6440	668
+906	6446	661
+907	6454	653
+908	6461	646
+909	6468	639
+910	6475	632
+911	6481	625
+912	6488	618
+913	6495	611
+914	6502	604
+915	6510	597
+916	6517	589
+917	6524	582
+918	6531	575
+919	6538	568
+920	6545	561
+921	6551	554
+922	6558	547
+923	6565	540
+924	6571	532
+925	6578	525
+926	6586	518
+927	6592	511
+928	6600	504
+929	6607	497
+930	6614	490
+931	6621	483
+932	6628	476
+933	6636	468
+934	6643	461
+935	6650	454
+936	6657	447
+937	6664	440
+938	6671	433
+939	6678	426
+940	6685	419
+941	6693	412
+942	6700	405
+943	6707	397
+944	6714	390
+945	6721	383
+946	6727	376
+947	6734	369
+948	6741	362
+949	6748	355
+950	6756	348
+951	6762	340
+952	6769	333
+953	6776	326
+954	6784	319
+955	6791	312
+956	6799	305
+957	6806	298
+958	6812	291
+959	6819	284
+960	6826	277
+961	6833	269
+962	6839	262
+963	6846	255
+964	6853	248
+965	6861	241
+966	6869	234
+967	6875	227
+968	6883	220
+969	6890	213
+970	6896	205
+971	6903	198
+972	6910	191
+973	6917	184
+974	6924	177
+975	6931	170
+976	6938	163
+977	6945	156
+978	6953	149
+979	6960	142
+980	6967	134
+981	6973	127
+982	6979	120
+983	6986	113
+984	6993	106
+985	6999	99
+986	7006	92
+987	7014	85
+988	7021	78
+989	7030	71
+990	7039	63
+991	7048	56
+992	7055	49
+993	7063	42
+994	7070	35
+995	7076	28
+996	7083	21
+997	7090	14
+998	7097	7
+999	7103	0
diff --git a/stoneforge/tests/tests_ml/catboost_info/tmp/cat_feature_index.3d8b762c-7ee93f40-8578f2ee-d9f3936a.tmp b/stoneforge/tests/tests_ml/catboost_info/tmp/cat_feature_index.3d8b762c-7ee93f40-8578f2ee-d9f3936a.tmp
new file mode 100644
index 0000000..593f470
Binary files /dev/null and b/stoneforge/tests/tests_ml/catboost_info/tmp/cat_feature_index.3d8b762c-7ee93f40-8578f2ee-d9f3936a.tmp differ
diff --git a/stoneforge/tests/tests_ml/decision_tree_classifier_fit_property.pkl b/stoneforge/tests/tests_ml/decision_tree_classifier_fit_property.pkl
new file mode 100644
index 0000000..8a0a0dd
Binary files /dev/null and b/stoneforge/tests/tests_ml/decision_tree_classifier_fit_property.pkl differ
diff --git a/stoneforge/tests/tests_ml/decision_tree_classifier_settings.json b/stoneforge/tests/tests_ml/decision_tree_classifier_settings.json
new file mode 100644
index 0000000..9e26dfe
--- /dev/null
+++ b/stoneforge/tests/tests_ml/decision_tree_classifier_settings.json
@@ -0,0 +1,1 @@
+{}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/evaluation_metrics.json b/stoneforge/tests/tests_ml/evaluation_metrics.json
new file mode 100644
index 0000000..e1e55e0
--- /dev/null
+++ b/stoneforge/tests/tests_ml/evaluation_metrics.json
@@ -0,0 +1,1 @@
+{"accuracy_score": 0.97926, "facies": [57.0, 49.0, 54.0, 25.0], "precision_recall_fscore": [["0.99457", "0.9864", "0.89575", "0.93634"], ["0.99032", "0.99089", "0.92247", "0.91927"], ["0.99244", "0.98864", "0.90891", "0.92773"], ["3513", "3075", "503", "768"]], "confusion_matrix": [["3479", "0", "34", "0"], ["0", "3047", "0", "28"], ["19", "0", "464", "20"], ["0", "42", "20", "706"]]}
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/first_steps_ml.py b/stoneforge/tests/tests_ml/first_steps_ml.py
new file mode 100644
index 0000000..33177f9
--- /dev/null
+++ b/stoneforge/tests/tests_ml/first_steps_ml.py
@@ -0,0 +1,47 @@
+# %%
+
+# conda create -n forgeml python=3.8.8 pip & conda activate forgeml
+# conda install -c anaconda jupyter
+# para remover ambiente
+# -> conda env remove -n forgeml
+
+import numpy as np
+import sys
+import os
+
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+
+if __package__:
+    from ..machine_learning import *
+else:
+    print('passed')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import machine_learning
+
+# %%
+
+iris = datasets.load_iris()
+X = iris.data[:, :2]  # we only take the first two features.
+y = iris.target
+n = len(set(y))
+
+print(np.shape(X))
+print(np.shape(y))
+print(n)
+
+X_train, X_test, y_train, y_test = train_test_split(X, y)
+
+# %%
+
+machine_learning.settings(method = "GaussianNB", path = "ml_sets", priors=[0.33, 0.33, 0.34])
+
+# %%
+
+machine_learning.fit(method = "GaussianNB", path = "ml_sets\\", X = X_train, y = y_train)
+
+# %%
+
+classification = machine_learning.predict(method = "GaussianNB", path = "ml_sets\\", x = X_test)
+
+# %%
\ No newline at end of file
diff --git a/stoneforge/tests/tests_ml/gaussian_naive_bayes_fit_property.pkl b/stoneforge/tests/tests_ml/gaussian_naive_bayes_fit_property.pkl
new file mode 100644
index 0000000..7a1e8a3
Binary files /dev/null and b/stoneforge/tests/tests_ml/gaussian_naive_bayes_fit_property.pkl differ
diff --git a/stoneforge/tests/tests_ml/scaler.pkl b/stoneforge/tests/tests_ml/scaler.pkl
new file mode 100644
index 0000000..f2aaec3
Binary files /dev/null and b/stoneforge/tests/tests_ml/scaler.pkl differ
diff --git a/stoneforge/tests/tests_ml/scalerp.pkl b/stoneforge/tests/tests_ml/scalerp.pkl
new file mode 100644
index 0000000..fdc06dc
Binary files /dev/null and b/stoneforge/tests/tests_ml/scalerp.pkl differ
diff --git a/stoneforge/tests/tests_ml/validation_tests.py b/stoneforge/tests/tests_ml/validation_tests.py
new file mode 100644
index 0000000..c2c9922
--- /dev/null
+++ b/stoneforge/tests/tests_ml/validation_tests.py
@@ -0,0 +1,134 @@
+# %%
+### Validation tests for ml methods
+
+import numpy as np
+import sys
+import os
+import pandas
+
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+
+if __package__:
+    from ..machine_learning import *
+else:
+    print('passed ml')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import machine_learning
+
+if __package__:
+    from ..preprocessing import *
+else:
+    print('passed mgt')
+    sys.path.append(os.path.dirname(__file__) + '/..')
+    import preprocessing
+
+
+# %%
+### Importing well data
+
+#project = preprocessing.project("D:\\appy_projetos\\wells")
+project = preprocessing.project("C:\\Users\\joseaugustodias\\Desktop\\pocos")
+project.import_folder()
+project.import_several_wells()
+
+print("project data paths:",project.well_names_paths)
+
+
+#%%
+### Setting mnemonics for machine learning (choosing mnemonics and replace similar ones)
+
+mnemonics_replacement = {
+    'DEPTH':['DEPTH'],
+    'GR':['GR'],
+    'CAL':['CAL','DCAL','HCAL','CALI'],
+    'RHOB':["RHOB","RHOZ","RHLA","RHBA","RHLA3","RHBA4"],
+    'RES':["ILD","HDRS","RT","AHT901","AT90","RT90"],
+    'NPHI':['NPHI'],
+    'Lithology':['Lith_new']
+}
+
+ref_mnemonics = list(mnemonics_replacement.keys())
+
+print("mnemonics of reference",ref_mnemonics)
+
+project.data_replacement(mnemonics_replacement)
+project.convert_into_matrix(ref_mnemonics)
+
+# %%
+### Spliting data (by wells) into training (tw_data) and validation (vw_data)
+### also incorporating all the training data into a single matrix
+
+tw_data,vw_data = preprocessing.well_train_test_split(['7-MP-22-BA','7-MP-50D-BA'],project.well_data)
+
+mega_data = preprocessing.data_assemble(tw_data,'data')
+print("training matrix shape:",np.shape(mega_data))
+
+# %%
+### Removing dummies from data
+
+def _remove_dummies(data):
+    data_1 = np.array(data).T
+    data_2 = data_1[~np.isnan(data_1).any(axis=1)]
+
+    return data_2
+
+mega_data = _remove_dummies(mega_data)
+
+print("training matrix shape (without dummies):",np.shape(mega_data))
+
+# %%
+### Selecting lithology (target) and well log data (forecasters) for training
+
+y = mega_data[:,-1]
+X = np.delete(mega_data,(-1), axis=1)
+
+# %%
+### preprocessing data for training
+
+data_processing = preprocessing.predict_processing(vw_data,'data')
+xy_raw = data_processing.matrix_values()
+
+y_v = {} # target data for validation
+x_v = {} # forecasters data for validation
+for well in xy_raw:
+    y_v[well] = xy_raw[well][:,-1]
+    x_v[well] = np.delete(xy_raw[well],(-1), axis=1)
+
+# %%
+###  Validation, training of data and classification
+
+machine_learning.validation(X, y, random_state = 2,n_splits = 10, path = "_ml_project")
+machine_learning.settings(method = "GaussianNB", path='_ml_project')
+machine_learning.fit(X,y,method = "GaussianNB", path = "_ml_project")
+
+class_db = {}
+for x in x_v:
+    class_db[x] = machine_learning.predict(x_v[x], method = "GaussianNB", path = "_ml_project")
+
+# %%
+### Method evaluation after classification
+
+print("lithology for classified 7-MP-22-BA well",class_db['7-MP-22-BA'],len(class_db['7-MP-22-BA']))
+print("lithology for original 7-MP-22-BA well",y_v['7-MP-22-BA'],len(y_v['7-MP-22-BA']))
+
+# %%
+
+print(class_db['7-MP-22-BA'],len(class_db['7-MP-22-BA']))
+print(y_v['7-MP-22-BA'],len(y_v['7-MP-22-BA']))
+# %%
+
+a = 0
+for i in range(len(class_db['7-MP-22-BA'])):
+    if class_db['7-MP-22-BA'][i] == y_v['7-MP-22-BA'][i]:
+        a += 1
+
+print(a)
+
+
+machine_learning.evaluation(y,y,"_ml_project")
+
+#print(json_dict)
+# %%
+len(a.return_curve(class_db)['7-MP-50D-BA'])
+# %%
\ No newline at end of file
diff --git a/stoneforge/tests_porosity/parameters_p.py b/stoneforge/tests/tests_porosity/parameters_p.py
similarity index 100%
rename from stoneforge/tests_porosity/parameters_p.py
rename to stoneforge/tests/tests_porosity/parameters_p.py
diff --git a/stoneforge/tests_porosity/test_porosity.py b/stoneforge/tests/tests_porosity/test_porosity.py
similarity index 100%
rename from stoneforge/tests_porosity/test_porosity.py
rename to stoneforge/tests/tests_porosity/test_porosity.py
diff --git a/stoneforge/tests_rock_physics/test_elastic_constants.py b/stoneforge/tests/tests_rock_physics/__init__.py
similarity index 100%
rename from stoneforge/tests_rock_physics/test_elastic_constants.py
rename to stoneforge/tests/tests_rock_physics/__init__.py
diff --git a/stoneforge/tests/tests_rock_physics/test_elastic_constants.py b/stoneforge/tests/tests_rock_physics/test_elastic_constants.py
new file mode 100644
index 0000000..e69de29
diff --git a/stoneforge/tests_rock_physics/test_fluid_substitution.py b/stoneforge/tests/tests_rock_physics/test_fluid_substitution.py
similarity index 100%
rename from stoneforge/tests_rock_physics/test_fluid_substitution.py
rename to stoneforge/tests/tests_rock_physics/test_fluid_substitution.py
diff --git a/stoneforge/tests_rock_physics/test_gem.py b/stoneforge/tests/tests_rock_physics/test_gem.py
similarity index 100%
rename from stoneforge/tests_rock_physics/test_gem.py
rename to stoneforge/tests/tests_rock_physics/test_gem.py
diff --git a/stoneforge/tests_water_saturation/parameters_ws.py b/stoneforge/tests/tests_water_saturation/parameters_ws.py
similarity index 94%
rename from stoneforge/tests_water_saturation/parameters_ws.py
rename to stoneforge/tests/tests_water_saturation/parameters_ws.py
index 8d5c7c7..c2eb916 100644
--- a/stoneforge/tests_water_saturation/parameters_ws.py
+++ b/stoneforge/tests/tests_water_saturation/parameters_ws.py
@@ -11,10 +11,10 @@ def __init__(self):
     config_water_saturarion = {
     "rw":(1.1,5.0,"f"),
     "rt":(1.1,5.0,"c"),
-    "phi":(0.0,1.0,"c"),
+    "phi":(0.0,2.65,"c"),
     "a":(0.0,1.0,"f"),
-    "m":(1.0,4.0,"f"),
-    "n":(2.0,3.0,"f"),
+    "m":(0.0,1.0,"f"),
+    "n":(0.0,1.0,"f"),
     }
 
     def sorted_values (configuration, size = 15, curve_size = 30, seed = 99):
diff --git a/stoneforge/tests_water_saturation/test_water_saturation.py b/stoneforge/tests/tests_water_saturation/test_water_saturation.py
similarity index 100%
rename from stoneforge/tests_water_saturation/test_water_saturation.py
rename to stoneforge/tests/tests_water_saturation/test_water_saturation.py