diff --git a/Examples/BatteryStateful.ipynb b/Examples/BatteryStateful.ipynb
index b9486ed..7301ddc 100644
--- a/Examples/BatteryStateful.ipynb
+++ b/Examples/BatteryStateful.ipynb
@@ -9,7 +9,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "7.0.0\n"
+      "7.1.0\n"
      ]
     }
    ],
@@ -94,7 +94,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1232c1b20>]"
+       "[<matplotlib.lines.Line2D at 0x1093c2000>]"
       ]
      },
      "execution_count": 3,
@@ -103,7 +103,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -136,7 +136,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1232fc530>"
+       "<matplotlib.legend.Legend at 0x10944e990>"
       ]
      },
      "execution_count": 4,
@@ -145,7 +145,7 @@
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
diff --git a/Examples/BatteryStateful_CustomLifeModel.ipynb b/Examples/BatteryStateful_CustomLifeModel.ipynb
index 391fd08..671a613 100644
--- a/Examples/BatteryStateful_CustomLifeModel.ipynb
+++ b/Examples/BatteryStateful_CustomLifeModel.ipynb
@@ -9,7 +9,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "7.0.0\n"
+      "7.1.0\n"
      ]
     }
    ],
diff --git a/Examples/BatteryWithCustomDispatch.py b/Examples/BatteryWithCustomDispatch.py
index 354155f..daf5430 100644
--- a/Examples/BatteryWithCustomDispatch.py
+++ b/Examples/BatteryWithCustomDispatch.py
@@ -4,7 +4,7 @@
 
 Additional financial models, inputs, and outputs can be found at https://nrel-pysam.readthedocs.io/en/master/modules/Battery.html
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 
 @author: brtietz
 """
diff --git a/Examples/FetchResourceFileExample.py b/Examples/FetchResourceFileExample.py
index 2f6dcc8..d19a851 100644
--- a/Examples/FetchResourceFileExample.py
+++ b/Examples/FetchResourceFileExample.py
@@ -10,7 +10,7 @@
 To use the `FetchResourceFile` function, register an email address to receive a
 free API key at at https://developer.nrel.gov/signup/.
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 
 @authors: skoeb, cpaulgilman
 '''
diff --git a/Examples/GenericSystemSingleOwnerExample.py b/Examples/GenericSystemSingleOwnerExample.py
index c2f95bb..9f44f1d 100755
--- a/Examples/GenericSystemSingleOwnerExample.py
+++ b/Examples/GenericSystemSingleOwnerExample.py
@@ -3,18 +3,19 @@
 """
 Created on Wed Mar  4 13:47:58 2020
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 
 @author: frohro
 """
 import json
+from pathlib import Path
 import PySAM.CustomGeneration as CustomGeneration
 import PySAM.Grid as Grid
 import PySAM.Singleowner as Singleowner
 import PySAM.PySSC as pssc
 
 ssc = pssc.PySSC()
-with open("Examples/100mW_Generic.json") as f:
+with open(Path(__file__).parent / "100mW_Generic.json") as f:
     dic = json.load(f)
     gs_dat = pssc.dict_to_ssc_table(dic, "custom_generation")
     grid_dat = pssc.dict_to_ssc_table(dic, "grid")
diff --git a/Examples/LoadToolsExample.py b/Examples/LoadToolsExample.py
index 9bbdeea..8354d74 100644
--- a/Examples/LoadToolsExample.py
+++ b/Examples/LoadToolsExample.py
@@ -7,7 +7,7 @@
 """
 A usage example for LoadTools.get_monthly peaks with hourly annual data
 Requires PySAM 4.2.0 or greater
-Recently tested with 7.0.0
+Recently tested with 7.1.0
 """
 if __name__ == "__main__":
     df = pd.read_csv(str(Path(__file__).parent / "sample_load.csv"), dtype=float)
diff --git a/Examples/Marine_energy_examples/WaveFileReader_example.ipynb b/Examples/Marine_energy_examples/WaveFileReader_example.ipynb
index a2f75b0..1f77b0d 100644
--- a/Examples/Marine_energy_examples/WaveFileReader_example.ipynb
+++ b/Examples/Marine_energy_examples/WaveFileReader_example.ipynb
@@ -20,7 +20,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "6.0.0\n"
+      "7.1.0\n"
      ]
     }
    ],
@@ -141,7 +141,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pysam_build_3.10",
+   "display_name": "pysam_build_3.12",
    "language": "python",
    "name": "python3"
   },
@@ -155,7 +155,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/Examples/NonAnnualSimulation.ipynb b/Examples/NonAnnualSimulation.ipynb
index 4a2b43f..ca2ae83 100644
--- a/Examples/NonAnnualSimulation.ipynb
+++ b/Examples/NonAnnualSimulation.ipynb
@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Most recently tested against PySAM 7.0.0\n",
+    "# Most recently tested against PySAM 7.1.0\n",
     "\n",
     "import pandas as pd\n",
     "import json\n",
diff --git a/Examples/PVPMC_pvlib_PySAM_example/PV_production.csv b/Examples/PVPMC_pvlib_PySAM_example/PV_production.csv
index 5febbdc..d3d7716 100644
--- a/Examples/PVPMC_pvlib_PySAM_example/PV_production.csv
+++ b/Examples/PVPMC_pvlib_PySAM_example/PV_production.csv
@@ -55,7 +55,7 @@ utc_time,0
 1990-01-03 05:00:00-07:00,-1.884
 1990-01-03 06:00:00-07:00,-1.884
 1990-01-03 07:00:00-07:00,-1.884
-1990-01-03 08:00:00-07:00,40897.20830733612
+1990-01-03 08:00:00-07:00,40897.20830733609
 1990-01-03 09:00:00-07:00,55792.12137429134
 1990-01-03 10:00:00-07:00,57631.72519847545
 1990-01-03 11:00:00-07:00,48814.41311163156
@@ -128,13 +128,13 @@ utc_time,0
 1990-01-06 06:00:00-07:00,-1.884
 1990-01-06 07:00:00-07:00,-1.884
 1990-01-06 08:00:00-07:00,35719.339342716194
-1990-01-06 09:00:00-07:00,48638.829649084095
+1990-01-06 09:00:00-07:00,48638.829649084044
 1990-01-06 10:00:00-07:00,55647.77317981144
 1990-01-06 11:00:00-07:00,68698.03716006744
 1990-01-06 12:00:00-07:00,67255.62930460078
 1990-01-06 13:00:00-07:00,62596.28612728737
 1990-01-06 14:00:00-07:00,51947.5722772804
-1990-01-06 15:00:00-07:00,32460.50860365693
+1990-01-06 15:00:00-07:00,32460.508603656937
 1990-01-06 16:00:00-07:00,9331.655356466752
 1990-01-06 17:00:00-07:00,-1.884
 1990-01-06 18:00:00-07:00,-1.884
@@ -175,12 +175,12 @@ utc_time,0
 1990-01-08 05:00:00-07:00,-1.884
 1990-01-08 06:00:00-07:00,-1.884
 1990-01-08 07:00:00-07:00,-1.884
-1990-01-08 08:00:00-07:00,44799.807227727964
+1990-01-08 08:00:00-07:00,44799.807227727935
 1990-01-08 09:00:00-07:00,55744.46665858531
 1990-01-08 10:00:00-07:00,63223.03308177484
 1990-01-08 11:00:00-07:00,68573.42049609474
 1990-01-08 12:00:00-07:00,68263.13558835644
-1990-01-08 13:00:00-07:00,63613.711829851614
+1990-01-08 13:00:00-07:00,63613.71182985163
 1990-01-08 14:00:00-07:00,53210.17833670527
 1990-01-08 15:00:00-07:00,36479.94216425571
 1990-01-08 16:00:00-07:00,13464.743478762512
@@ -224,7 +224,7 @@ utc_time,0
 1990-01-10 06:00:00-07:00,-1.884
 1990-01-10 07:00:00-07:00,-1.884
 1990-01-10 08:00:00-07:00,39954.14941163812
-1990-01-10 09:00:00-07:00,48458.70464728278
+1990-01-10 09:00:00-07:00,48458.70464728277
 1990-01-10 10:00:00-07:00,51796.07543868913
 1990-01-10 11:00:00-07:00,48236.85176424997
 1990-01-10 12:00:00-07:00,48113.43029599154
@@ -272,7 +272,7 @@ utc_time,0
 1990-01-12 06:00:00-07:00,-1.884
 1990-01-12 07:00:00-07:00,-1.884
 1990-01-12 08:00:00-07:00,44213.958748969846
-1990-01-12 09:00:00-07:00,55531.18481809181
+1990-01-12 09:00:00-07:00,55531.184818091744
 1990-01-12 10:00:00-07:00,65035.37637340204
 1990-01-12 11:00:00-07:00,70308.8242829142
 1990-01-12 12:00:00-07:00,70436.11525252504
@@ -295,13 +295,13 @@ utc_time,0
 1990-01-13 05:00:00-07:00,-1.884
 1990-01-13 06:00:00-07:00,-1.884
 1990-01-13 07:00:00-07:00,-1.884
-1990-01-13 08:00:00-07:00,43902.549710573054
+1990-01-13 08:00:00-07:00,43902.54971057301
 1990-01-13 09:00:00-07:00,55334.936750832334
 1990-01-13 10:00:00-07:00,64530.283182338244
 1990-01-13 11:00:00-07:00,69450.61043772518
 1990-01-13 12:00:00-07:00,69392.11978826021
 1990-01-13 13:00:00-07:00,64373.778040235666
-1990-01-13 14:00:00-07:00,53836.93302599179
+1990-01-13 14:00:00-07:00,53836.933025991806
 1990-01-13 15:00:00-07:00,37524.24730374875
 1990-01-13 16:00:00-07:00,15029.146938324524
 1990-01-13 17:00:00-07:00,-1.884
@@ -324,9 +324,9 @@ utc_time,0
 1990-01-14 10:00:00-07:00,61352.66499962558
 1990-01-14 11:00:00-07:00,67766.86487203385
 1990-01-14 12:00:00-07:00,68417.10874278816
-1990-01-14 13:00:00-07:00,62394.87359188625
+1990-01-14 13:00:00-07:00,62394.87359188624
 1990-01-14 14:00:00-07:00,44578.900374965255
-1990-01-14 15:00:00-07:00,19208.823463796176
+1990-01-14 15:00:00-07:00,19208.823463796187
 1990-01-14 16:00:00-07:00,13174.182933913602
 1990-01-14 17:00:00-07:00,-1.884
 1990-01-14 18:00:00-07:00,-1.884
@@ -420,11 +420,11 @@ utc_time,0
 1990-01-18 10:00:00-07:00,47899.73921844148
 1990-01-18 11:00:00-07:00,51043.0131717457
 1990-01-18 12:00:00-07:00,54297.82187340318
-1990-01-18 13:00:00-07:00,44412.926401929275
-1990-01-18 14:00:00-07:00,30993.170082326473
+1990-01-18 13:00:00-07:00,44412.92640192926
+1990-01-18 14:00:00-07:00,30993.17008232648
 1990-01-18 15:00:00-07:00,22608.907380234854
-1990-01-18 16:00:00-07:00,13836.362760369184
-1990-01-18 17:00:00-07:00,272.93871553847833
+1990-01-18 16:00:00-07:00,13836.362760369195
+1990-01-18 17:00:00-07:00,272.93871553847924
 1990-01-18 18:00:00-07:00,-1.884
 1990-01-18 19:00:00-07:00,-1.884
 1990-01-18 20:00:00-07:00,-1.884
@@ -439,7 +439,7 @@ utc_time,0
 1990-01-19 05:00:00-07:00,-1.884
 1990-01-19 06:00:00-07:00,-1.884
 1990-01-19 07:00:00-07:00,-1.884
-1990-01-19 08:00:00-07:00,44533.55888144308
+1990-01-19 08:00:00-07:00,44533.558881443125
 1990-01-19 09:00:00-07:00,57605.522101171984
 1990-01-19 10:00:00-07:00,68129.25889051147
 1990-01-19 11:00:00-07:00,72938.6454659393
@@ -464,7 +464,7 @@ utc_time,0
 1990-01-20 06:00:00-07:00,-1.884
 1990-01-20 07:00:00-07:00,-1.884
 1990-01-20 08:00:00-07:00,42145.30240657296
-1990-01-20 09:00:00-07:00,52951.25486647061
+1990-01-20 09:00:00-07:00,52951.25486647063
 1990-01-20 10:00:00-07:00,56627.96602364376
 1990-01-20 11:00:00-07:00,65524.276586778986
 1990-01-20 12:00:00-07:00,63019.82455137827
@@ -487,8 +487,8 @@ utc_time,0
 1990-01-21 05:00:00-07:00,-1.884
 1990-01-21 06:00:00-07:00,-1.884
 1990-01-21 07:00:00-07:00,-1.884
-1990-01-21 08:00:00-07:00,36047.83625748935
-1990-01-21 09:00:00-07:00,53762.51057784748
+1990-01-21 08:00:00-07:00,36047.83625748938
+1990-01-21 09:00:00-07:00,53762.510577847475
 1990-01-21 10:00:00-07:00,67444.81915039221
 1990-01-21 11:00:00-07:00,69045.05700365377
 1990-01-21 12:00:00-07:00,66775.47038599162
@@ -514,9 +514,9 @@ utc_time,0
 1990-01-22 08:00:00-07:00,43576.64557130747
 1990-01-22 09:00:00-07:00,56968.489142176295
 1990-01-22 10:00:00-07:00,67552.83215301737
-1990-01-22 11:00:00-07:00,72904.87430603687
+1990-01-22 11:00:00-07:00,72904.87430603686
 1990-01-22 12:00:00-07:00,73092.8930608433
-1990-01-22 13:00:00-07:00,68270.093031537
+1990-01-22 13:00:00-07:00,68270.09303153699
 1990-01-22 14:00:00-07:00,57278.04951489529
 1990-01-22 15:00:00-07:00,38602.843616701415
 1990-01-22 16:00:00-07:00,10912.841833847708
@@ -542,7 +542,7 @@ utc_time,0
 1990-01-23 12:00:00-07:00,42151.051979708325
 1990-01-23 13:00:00-07:00,36982.99130751815
 1990-01-23 14:00:00-07:00,29774.040503448225
-1990-01-23 15:00:00-07:00,13747.249985794053
+1990-01-23 15:00:00-07:00,13747.249985794057
 1990-01-23 16:00:00-07:00,5521.518686171481
 1990-01-23 17:00:00-07:00,-1.884
 1990-01-23 18:00:00-07:00,-1.884
@@ -568,7 +568,7 @@ utc_time,0
 1990-01-24 14:00:00-07:00,32258.377212843803
 1990-01-24 15:00:00-07:00,25312.2728207301
 1990-01-24 16:00:00-07:00,13259.272405270005
-1990-01-24 17:00:00-07:00,474.54279481879803
+1990-01-24 17:00:00-07:00,474.54279481879877
 1990-01-24 18:00:00-07:00,-1.884
 1990-01-24 19:00:00-07:00,-1.884
 1990-01-24 20:00:00-07:00,-1.884
@@ -591,8 +591,8 @@ utc_time,0
 1990-01-25 13:00:00-07:00,63279.38602637075
 1990-01-25 14:00:00-07:00,48063.82205251364
 1990-01-25 15:00:00-07:00,33665.22421684879
-1990-01-25 16:00:00-07:00,18477.877650659088
-1990-01-25 17:00:00-07:00,975.1575329336915
+1990-01-25 16:00:00-07:00,18477.87765065909
+1990-01-25 17:00:00-07:00,975.157532933692
 1990-01-25 18:00:00-07:00,-1.884
 1990-01-25 19:00:00-07:00,-1.884
 1990-01-25 20:00:00-07:00,-1.884
@@ -688,7 +688,7 @@ utc_time,0
 1990-01-29 14:00:00-07:00,59141.35949668583
 1990-01-29 15:00:00-07:00,43417.58543147182
 1990-01-29 16:00:00-07:00,21339.07676016225
-1990-01-29 17:00:00-07:00,1424.7854360221197
+1990-01-29 17:00:00-07:00,1424.785436022119
 1990-01-29 18:00:00-07:00,-1.884
 1990-01-29 19:00:00-07:00,-1.884
 1990-01-29 20:00:00-07:00,-1.884
@@ -703,15 +703,15 @@ utc_time,0
 1990-01-30 05:00:00-07:00,-1.884
 1990-01-30 06:00:00-07:00,-1.884
 1990-01-30 07:00:00-07:00,-1.884
-1990-01-30 08:00:00-07:00,42190.39290679442
-1990-01-30 09:00:00-07:00,56274.65220638223
+1990-01-30 08:00:00-07:00,42190.39290679445
+1990-01-30 09:00:00-07:00,56274.65220638222
 1990-01-30 10:00:00-07:00,66905.16189389194
 1990-01-30 11:00:00-07:00,72740.7453647084
 1990-01-30 12:00:00-07:00,73121.5357187518
 1990-01-30 13:00:00-07:00,68845.07377784365
 1990-01-30 14:00:00-07:00,59184.852183690076
 1990-01-30 15:00:00-07:00,43656.62641901908
-1990-01-30 16:00:00-07:00,21525.671793744572
+1990-01-30 16:00:00-07:00,21525.67179374457
 1990-01-30 17:00:00-07:00,1567.5462883763603
 1990-01-30 18:00:00-07:00,-1.884
 1990-01-30 19:00:00-07:00,-1.884
@@ -733,7 +733,7 @@ utc_time,0
 1990-01-31 11:00:00-07:00,71114.27549326158
 1990-01-31 12:00:00-07:00,71942.76324455731
 1990-01-31 13:00:00-07:00,66321.47933551163
-1990-01-31 14:00:00-07:00,58637.46042451057
+1990-01-31 14:00:00-07:00,58637.46042451056
 1990-01-31 15:00:00-07:00,42225.16235689224
 1990-01-31 16:00:00-07:00,19002.741545092773
 1990-01-31 17:00:00-07:00,1848.492143772335
@@ -752,8 +752,8 @@ utc_time,0
 1990-02-01 06:00:00-07:00,-1.884
 1990-02-01 07:00:00-07:00,-1.884
 1990-02-01 08:00:00-07:00,39089.63025218394
-1990-02-01 09:00:00-07:00,51711.81566954587
-1990-02-01 10:00:00-07:00,58794.05812047055
+1990-02-01 09:00:00-07:00,51711.81566954584
+1990-02-01 10:00:00-07:00,58794.058120470574
 1990-02-01 11:00:00-07:00,59125.04316523214
 1990-02-01 12:00:00-07:00,67841.32747379178
 1990-02-01 13:00:00-07:00,65759.25681407526
@@ -784,7 +784,7 @@ utc_time,0
 1990-02-02 14:00:00-07:00,52819.46952853906
 1990-02-02 15:00:00-07:00,38851.34651854562
 1990-02-02 16:00:00-07:00,18686.38024979989
-1990-02-02 17:00:00-07:00,1310.6679139936102
+1990-02-02 17:00:00-07:00,1310.6679139936116
 1990-02-02 18:00:00-07:00,-1.884
 1990-02-02 19:00:00-07:00,-1.884
 1990-02-02 20:00:00-07:00,-1.884
@@ -802,10 +802,10 @@ utc_time,0
 1990-02-03 08:00:00-07:00,33296.73498095627
 1990-02-03 09:00:00-07:00,49595.377884464615
 1990-02-03 10:00:00-07:00,59849.01223838077
-1990-02-03 11:00:00-07:00,37432.63309937376
+1990-02-03 11:00:00-07:00,37432.63309937375
 1990-02-03 12:00:00-07:00,20057.77369564204
 1990-02-03 13:00:00-07:00,11915.425998706769
-1990-02-03 14:00:00-07:00,17840.290887789237
+1990-02-03 14:00:00-07:00,17840.29088778923
 1990-02-03 15:00:00-07:00,22129.06429494225
 1990-02-03 16:00:00-07:00,12067.760480533681
 1990-02-03 17:00:00-07:00,666.0945626878348
@@ -831,7 +831,7 @@ utc_time,0
 1990-02-04 13:00:00-07:00,69548.81250885746
 1990-02-04 14:00:00-07:00,59709.3058075777
 1990-02-04 15:00:00-07:00,44185.6178283948
-1990-02-04 16:00:00-07:00,23029.080298307363
+1990-02-04 16:00:00-07:00,23029.080298307355
 1990-02-04 17:00:00-07:00,2379.3487741222975
 1990-02-04 18:00:00-07:00,-1.884
 1990-02-04 19:00:00-07:00,-1.884
@@ -848,7 +848,7 @@ utc_time,0
 1990-02-05 06:00:00-07:00,-1.884
 1990-02-05 07:00:00-07:00,-1.884
 1990-02-05 08:00:00-07:00,40513.61835485927
-1990-02-05 09:00:00-07:00,55951.831213698606
+1990-02-05 09:00:00-07:00,55951.83121369863
 1990-02-05 10:00:00-07:00,67120.29875288671
 1990-02-05 11:00:00-07:00,73127.38660313278
 1990-02-05 12:00:00-07:00,73900.06818459227
@@ -895,8 +895,8 @@ utc_time,0
 1990-02-07 05:00:00-07:00,-1.884
 1990-02-07 06:00:00-07:00,-1.884
 1990-02-07 07:00:00-07:00,-1.884
-1990-02-07 08:00:00-07:00,40550.14501383405
-1990-02-07 09:00:00-07:00,55833.28491148212
+1990-02-07 08:00:00-07:00,40550.14501383402
+1990-02-07 09:00:00-07:00,55833.284911482035
 1990-02-07 10:00:00-07:00,66579.2390641075
 1990-02-07 11:00:00-07:00,72395.9026255335
 1990-02-07 12:00:00-07:00,73024.78638758516
@@ -904,7 +904,7 @@ utc_time,0
 1990-02-07 14:00:00-07:00,60059.95733021711
 1990-02-07 15:00:00-07:00,44956.65221683998
 1990-02-07 16:00:00-07:00,23996.786948536934
-1990-02-07 17:00:00-07:00,2832.413915472085
+1990-02-07 17:00:00-07:00,2832.4139154720874
 1990-02-07 18:00:00-07:00,-1.884
 1990-02-07 19:00:00-07:00,-1.884
 1990-02-07 20:00:00-07:00,-1.884
@@ -920,12 +920,12 @@ utc_time,0
 1990-02-08 06:00:00-07:00,-1.884
 1990-02-08 07:00:00-07:00,-1.884
 1990-02-08 08:00:00-07:00,40904.09840657138
-1990-02-08 09:00:00-07:00,56095.48480280094
+1990-02-08 09:00:00-07:00,56095.48480280092
 1990-02-08 10:00:00-07:00,66796.22349843786
 1990-02-08 11:00:00-07:00,72316.31249178622
 1990-02-08 12:00:00-07:00,72468.3838502967
 1990-02-08 13:00:00-07:00,68451.00790167374
-1990-02-08 14:00:00-07:00,59615.63951771441
+1990-02-08 14:00:00-07:00,59615.63951771439
 1990-02-08 15:00:00-07:00,44620.75028117767
 1990-02-08 16:00:00-07:00,23791.44986373021
 1990-02-08 17:00:00-07:00,2829.2585492847843
@@ -943,7 +943,7 @@ utc_time,0
 1990-02-09 05:00:00-07:00,-1.884
 1990-02-09 06:00:00-07:00,-1.884
 1990-02-09 07:00:00-07:00,-1.884
-1990-02-09 08:00:00-07:00,39270.629167376625
+1990-02-09 08:00:00-07:00,39270.62916737663
 1990-02-09 09:00:00-07:00,54374.944847278006
 1990-02-09 10:00:00-07:00,65398.74091790997
 1990-02-09 11:00:00-07:00,70721.80495504852
@@ -967,9 +967,9 @@ utc_time,0
 1990-02-10 05:00:00-07:00,-1.884
 1990-02-10 06:00:00-07:00,-1.884
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 1990-02-11 17:00:00-07:00,3325.9258755209653
 1990-02-11 18:00:00-07:00,-1.884
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 1990-02-12 19:00:00-07:00,-1.884
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 1990-02-13 18:00:00-07:00,-1.884
 1990-02-13 19:00:00-07:00,-1.884
 1990-02-13 20:00:00-07:00,-1.884
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 1990-02-14 19:00:00-07:00,-1.884
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 1990-02-15 18:00:00-07:00,-1.884
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 1990-02-20 18:00:00-07:00,-1.884
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 1990-02-25 19:00:00-07:00,-1.884
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 1990-03-29 09:00:00-07:00,57828.903233092184
 1990-03-29 10:00:00-07:00,68402.95664521406
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 1990-03-29 14:00:00-07:00,60492.674034456584
 1990-03-29 15:00:00-07:00,46787.4304804386
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 1990-03-29 18:00:00-07:00,-1.884
 1990-03-29 19:00:00-07:00,-1.884
 1990-03-29 20:00:00-07:00,-1.884
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 1990-03-31 13:00:00-07:00,66844.15077629384
 1990-03-31 14:00:00-07:00,55685.23843272062
 1990-03-31 15:00:00-07:00,41896.19144558869
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 1990-03-31 18:00:00-07:00,-1.884
 1990-03-31 19:00:00-07:00,-1.884
 1990-03-31 20:00:00-07:00,-1.884
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 1990-04-01 06:00:00-07:00,550.9665725986503
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 1990-04-02 05:00:00-07:00,-1.884
 1990-04-02 06:00:00-07:00,1592.7101551949338
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 1990-04-02 19:00:00-07:00,-1.884
 1990-04-02 20:00:00-07:00,-1.884
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 1990-04-04 20:00:00-07:00,-1.884
 1990-04-04 21:00:00-07:00,-1.884
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 1990-04-06 20:00:00-07:00,-1.884
 1990-04-06 21:00:00-07:00,-1.884
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 1990-04-08 20:00:00-07:00,-1.884
 1990-04-08 21:00:00-07:00,-1.884
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 1990-04-09 19:00:00-07:00,-1.884
 1990-04-09 20:00:00-07:00,-1.884
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 1990-04-11 20:00:00-07:00,-1.884
 1990-04-11 21:00:00-07:00,-1.884
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 1990-04-12 14:00:00-07:00,51758.82979798774
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 1990-04-12 19:00:00-07:00,-1.884
 1990-04-12 20:00:00-07:00,-1.884
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 1990-04-14 12:00:00-07:00,69163.07929346857
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 1990-04-14 20:00:00-07:00,-1.884
 1990-04-14 21:00:00-07:00,-1.884
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 1990-04-15 21:00:00-07:00,-1.884
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 1990-04-16 19:00:00-07:00,-1.884
 1990-04-16 20:00:00-07:00,-1.884
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 1990-04-17 15:00:00-07:00,41725.046630278106
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 1990-04-17 20:00:00-07:00,-1.884
 1990-04-17 21:00:00-07:00,-1.884
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 1990-04-19 07:00:00-07:00,16279.851609455629
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 1990-04-21 15:00:00-07:00,44594.71095507927
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 1990-04-22 19:00:00-07:00,-1.884
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 1990-04-24 13:00:00-07:00,65040.1118645
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 1990-04-24 19:00:00-07:00,-1.884
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 1990-04-25 12:00:00-07:00,23646.5005174302
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 1990-04-30 15:00:00-07:00,46408.01308602395
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 1990-05-03 11:00:00-07:00,67348.56136831534
 1990-05-03 12:00:00-07:00,67607.06663921538
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 1990-05-03 14:00:00-07:00,54883.12526903854
 1990-05-03 15:00:00-07:00,41423.82621144636
 1990-05-03 16:00:00-07:00,23567.292525419503
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 1990-05-03 19:00:00-07:00,-1.884
 1990-05-03 20:00:00-07:00,-1.884
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 1990-05-04 05:00:00-07:00,-1.884
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 1990-05-04 16:00:00-07:00,22342.646533806044
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 1990-05-04 19:00:00-07:00,-1.884
 1990-05-04 20:00:00-07:00,-1.884
 1990-05-04 21:00:00-07:00,-1.884
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 1990-05-05 04:00:00-07:00,-1.884
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 1990-05-05 06:00:00-07:00,601.9862766252012
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 1990-05-05 10:00:00-07:00,56781.61381972801
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 1990-05-07 06:00:00-07:00,643.8233462798852
 1990-05-07 07:00:00-07:00,16752.208334527404
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 1990-05-07 10:00:00-07:00,62977.72803276305
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 1990-05-07 19:00:00-07:00,-1.884
 1990-05-07 20:00:00-07:00,-1.884
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 1990-05-08 05:00:00-07:00,-1.884
 1990-05-08 06:00:00-07:00,4932.542290727371
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 1990-05-08 13:00:00-07:00,44250.97998119025
 1990-05-08 14:00:00-07:00,45627.199260385365
 1990-05-08 15:00:00-07:00,24520.35271327691
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 1990-05-08 19:00:00-07:00,-1.884
 1990-05-08 20:00:00-07:00,-1.884
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 1990-05-09 04:00:00-07:00,-1.884
 1990-05-09 05:00:00-07:00,-1.884
 1990-05-09 06:00:00-07:00,3798.853629902006
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 1990-05-09 09:00:00-07:00,38866.013499024186
 1990-05-09 10:00:00-07:00,49569.088444111185
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 1990-05-09 13:00:00-07:00,46233.344169806005
 1990-05-09 14:00:00-07:00,44567.50519464519
 1990-05-09 15:00:00-07:00,33355.30762550924
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 1990-05-09 20:00:00-07:00,-1.884
 1990-05-09 21:00:00-07:00,-1.884
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 1990-05-10 04:00:00-07:00,-1.884
 1990-05-10 05:00:00-07:00,-1.884
 1990-05-10 06:00:00-07:00,631.7359385827501
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 1990-05-10 09:00:00-07:00,50819.99704935055
 1990-05-10 10:00:00-07:00,59809.119793711354
 1990-05-10 11:00:00-07:00,63958.62484361242
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 1990-05-10 15:00:00-07:00,38418.33888783443
 1990-05-10 16:00:00-07:00,20969.336933584585
 1990-05-10 17:00:00-07:00,8691.585935838079
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 1990-05-10 19:00:00-07:00,-1.884
 1990-05-10 20:00:00-07:00,-1.884
 1990-05-10 21:00:00-07:00,-1.884
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 1990-05-11 05:00:00-07:00,-1.884
 1990-05-11 06:00:00-07:00,694.775861105521
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 1990-05-11 13:00:00-07:00,52965.98324551905
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 1990-05-11 15:00:00-07:00,39437.77678318695
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 1990-05-11 17:00:00-07:00,8477.077825999628
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 1990-05-11 19:00:00-07:00,-1.884
 1990-05-11 20:00:00-07:00,-1.884
 1990-05-11 21:00:00-07:00,-1.884
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 1990-05-12 14:00:00-07:00,51070.26005543536
 1990-05-12 15:00:00-07:00,40059.81659768706
 1990-05-12 16:00:00-07:00,25010.785598941307
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 1990-05-12 20:00:00-07:00,-1.884
 1990-05-12 21:00:00-07:00,-1.884
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 1990-05-13 05:00:00-07:00,-1.884
 1990-05-13 06:00:00-07:00,756.3687061761044
 1990-05-13 07:00:00-07:00,15292.536302649843
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 1990-05-13 11:00:00-07:00,63043.68227389469
 1990-05-13 12:00:00-07:00,62975.72396802441
 1990-05-13 13:00:00-07:00,60126.69172041782
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 1990-05-16 04:00:00-07:00,-1.884
 1990-05-16 05:00:00-07:00,-1.884
 1990-05-16 06:00:00-07:00,3628.3181579012735
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 1990-05-16 08:00:00-07:00,14986.474139308135
 1990-05-16 09:00:00-07:00,25298.28116867909
 1990-05-16 10:00:00-07:00,30775.937161927428
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 1990-05-17 05:00:00-07:00,-1.884
 1990-05-17 06:00:00-07:00,6947.3602307652845
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 1990-05-17 09:00:00-07:00,27557.476841568685
 1990-05-17 10:00:00-07:00,29748.466584908172
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 1990-05-17 13:00:00-07:00,36617.187687092395
 1990-05-17 14:00:00-07:00,43700.315028671095
 1990-05-17 15:00:00-07:00,28931.24366870566
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 1990-05-17 18:00:00-07:00,632.004900979484
 1990-05-17 19:00:00-07:00,-1.884
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 1990-05-18 05:00:00-07:00,-1.884
 1990-05-18 06:00:00-07:00,1220.1383804643083
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 1990-05-18 08:00:00-07:00,35156.65117535065
 1990-05-18 09:00:00-07:00,50360.28811212492
 1990-05-18 10:00:00-07:00,58420.51978962594
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 1990-05-18 18:00:00-07:00,764.4432279693619
 1990-05-18 19:00:00-07:00,-1.884
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 1990-05-19 04:00:00-07:00,-1.884
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 1990-05-19 06:00:00-07:00,928.7119818192712
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 1990-05-19 09:00:00-07:00,48166.48613478438
 1990-05-19 10:00:00-07:00,57733.38864115108
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 1990-05-19 14:00:00-07:00,45350.71996356098
 1990-05-19 15:00:00-07:00,33068.04193304217
 1990-05-19 16:00:00-07:00,15528.844762556208
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 1990-05-19 19:00:00-07:00,-1.884
 1990-05-19 20:00:00-07:00,-1.884
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 1990-05-21 04:00:00-07:00,-1.884
 1990-05-21 05:00:00-07:00,-1.884
 1990-05-21 06:00:00-07:00,2862.8577390612295
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 1990-05-21 10:00:00-07:00,58626.67301905952
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 1990-05-21 13:00:00-07:00,54818.065886643024
 1990-05-21 14:00:00-07:00,51073.13337063369
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 1990-05-21 20:00:00-07:00,-1.884
 1990-05-21 21:00:00-07:00,-1.884
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 1990-05-22 05:00:00-07:00,-1.884
 1990-05-22 06:00:00-07:00,761.0187717980916
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 1990-05-23 19:00:00-07:00,-1.884
 1990-05-23 20:00:00-07:00,-1.884
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 1990-05-24 19:00:00-07:00,-1.884
 1990-05-24 20:00:00-07:00,-1.884
 1990-05-24 21:00:00-07:00,-1.884
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 1990-05-25 05:00:00-07:00,-1.884
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 1990-05-25 10:00:00-07:00,55625.315701517815
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 1990-05-26 07:00:00-07:00,14276.741871556862
 1990-05-26 08:00:00-07:00,33080.98428156583
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 1990-05-26 13:00:00-07:00,55964.432286549156
 1990-05-26 14:00:00-07:00,50083.80444975688
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 1990-05-26 16:00:00-07:00,24345.531654699767
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 1990-05-26 18:00:00-07:00,1197.2940592312953
 1990-05-26 19:00:00-07:00,-1.884
 1990-05-26 20:00:00-07:00,-1.884
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 1990-05-27 04:00:00-07:00,-1.884
 1990-05-27 05:00:00-07:00,1797.6413199075591
 1990-05-27 06:00:00-07:00,5626.080792997575
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 1990-05-27 09:00:00-07:00,40633.276530116345
 1990-05-27 10:00:00-07:00,47391.13177456958
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 1990-05-28 14:00:00-07:00,50483.22188215221
 1990-05-28 15:00:00-07:00,39222.65950920827
 1990-05-28 16:00:00-07:00,24836.172339519235
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 1990-05-28 18:00:00-07:00,1244.7926030659328
 1990-05-28 19:00:00-07:00,-1.884
 1990-05-28 20:00:00-07:00,-1.884
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 1990-05-30 04:00:00-07:00,-1.884
 1990-05-30 05:00:00-07:00,1107.3961782971203
 1990-05-30 06:00:00-07:00,751.7792563334965
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 1990-05-30 12:00:00-07:00,65986.69668859485
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 1990-05-30 14:00:00-07:00,54114.978556469985
 1990-05-30 15:00:00-07:00,42042.42950824566
 1990-05-30 16:00:00-07:00,26542.51819710006
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 1990-05-31 14:00:00-07:00,49473.005340589116
 1990-05-31 15:00:00-07:00,39059.8467543346
 1990-05-31 16:00:00-07:00,24432.367909903292
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 1990-05-31 18:00:00-07:00,1074.5602244781812
 1990-05-31 19:00:00-07:00,-1.884
 1990-05-31 20:00:00-07:00,-1.884
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 1990-06-01 12:00:00-07:00,63608.708596849996
 1990-06-01 13:00:00-07:00,59996.65275785506
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 1990-06-01 16:00:00-07:00,25926.592274824012
 1990-06-01 17:00:00-07:00,9820.667822539126
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 1990-06-02 04:00:00-07:00,-1.884
 1990-06-02 05:00:00-07:00,1806.19456257118
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 1990-06-02 09:00:00-07:00,47366.689604339175
 1990-06-02 10:00:00-07:00,55931.70908150673
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 1990-06-03 10:00:00-07:00,55317.27141939514
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 1990-06-03 18:00:00-07:00,740.6154980106342
 1990-06-03 19:00:00-07:00,-1.884
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 1990-06-04 08:00:00-07:00,33002.525661018575
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 1990-06-04 20:00:00-07:00,-1.884
 1990-06-04 21:00:00-07:00,-1.884
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 1990-06-05 04:00:00-07:00,-1.884
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 1990-06-05 18:00:00-07:00,1137.3729506439838
 1990-06-05 19:00:00-07:00,-1.884
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 1990-06-06 07:00:00-07:00,13886.346368286933
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 1990-06-06 20:00:00-07:00,-1.884
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 1990-06-07 16:00:00-07:00,21623.868897764743
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 1990-06-07 19:00:00-07:00,-1.884
 1990-06-07 20:00:00-07:00,-1.884
 1990-06-07 21:00:00-07:00,-1.884
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 1990-06-09 05:00:00-07:00,1497.4941187207266
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 1990-06-10 04:00:00-07:00,-1.884
 1990-06-10 05:00:00-07:00,1172.5200851785523
 1990-06-10 06:00:00-07:00,2805.5429253846064
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 1990-06-10 09:00:00-07:00,45392.091467706865
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 1990-06-11 07:00:00-07:00,13371.22082346915
 1990-06-11 08:00:00-07:00,32632.72370912375
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 1990-06-11 14:00:00-07:00,50583.422082290206
 1990-06-11 15:00:00-07:00,39588.29863828888
 1990-06-11 16:00:00-07:00,25442.7275182692
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 1990-06-11 19:00:00-07:00,-1.884
 1990-06-11 20:00:00-07:00,-1.884
 1990-06-11 21:00:00-07:00,-1.884
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 1990-06-12 09:00:00-07:00,45545.68755581183
 1990-06-12 10:00:00-07:00,54283.16514688337
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 1990-06-12 14:00:00-07:00,42521.03204263126
 1990-06-12 15:00:00-07:00,37719.136182553484
 1990-06-12 16:00:00-07:00,24565.312993980555
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 1990-06-12 19:00:00-07:00,-1.884
 1990-06-12 20:00:00-07:00,-1.884
 1990-06-12 21:00:00-07:00,-1.884
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 1990-06-13 09:00:00-07:00,45423.210866969435
 1990-06-13 10:00:00-07:00,54815.125694029484
 1990-06-13 11:00:00-07:00,58382.573898123315
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 1990-06-13 13:00:00-07:00,49567.25207954772
 1990-06-13 14:00:00-07:00,39894.03326034109
 1990-06-13 15:00:00-07:00,25313.23689249296
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 1990-06-13 18:00:00-07:00,2099.753132467814
 1990-06-13 19:00:00-07:00,-1.884
 1990-06-13 20:00:00-07:00,-1.884
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 1990-06-15 14:00:00-07:00,27483.083568839236
 1990-06-15 15:00:00-07:00,23739.96370781046
 1990-06-15 16:00:00-07:00,13002.202435020621
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 1990-06-15 19:00:00-07:00,-1.884
 1990-06-15 20:00:00-07:00,-1.884
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 1990-06-16 15:00:00-07:00,31629.04154426141
 1990-06-16 16:00:00-07:00,18590.925550318087
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 1990-06-16 20:00:00-07:00,-1.884
 1990-06-16 21:00:00-07:00,-1.884
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 1990-06-17 06:00:00-07:00,2112.708069973341
 1990-06-17 07:00:00-07:00,12361.076208547465
 1990-06-17 08:00:00-07:00,30665.288559019285
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 1990-06-17 15:00:00-07:00,31361.057803440523
 1990-06-17 16:00:00-07:00,21251.101254069712
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 1990-06-18 04:00:00-07:00,-1.884
 1990-06-18 05:00:00-07:00,1129.003950085811
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 1990-06-18 09:00:00-07:00,46017.074241218994
 1990-06-18 10:00:00-07:00,55369.73993020358
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 1990-06-18 15:00:00-07:00,40293.53639387005
 1990-06-18 16:00:00-07:00,25927.34068118417
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 1990-06-18 20:00:00-07:00,-1.884
 1990-06-18 21:00:00-07:00,-1.884
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 1990-06-19 15:00:00-07:00,39967.20806279166
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 1990-06-19 20:00:00-07:00,-1.884
 1990-06-19 21:00:00-07:00,-1.884
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 1990-06-21 13:00:00-07:00,56073.12452241469
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 1990-06-22 09:00:00-07:00,45808.68700901329
 1990-06-22 10:00:00-07:00,54672.6220795007
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 1990-06-22 14:00:00-07:00,47465.87976444534
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 1990-06-22 19:00:00-07:00,-1.884
 1990-06-22 20:00:00-07:00,-1.884
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 1990-06-23 11:00:00-07:00,59453.56012448354
 1990-06-23 12:00:00-07:00,60498.98711572502
 1990-06-23 13:00:00-07:00,57572.754679359066
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 1990-06-23 15:00:00-07:00,39800.08088651659
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 1990-06-23 17:00:00-07:00,10535.039398205578
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 1990-06-24 05:00:00-07:00,1007.1586644770682
 1990-06-24 06:00:00-07:00,711.0946146806539
 1990-06-24 07:00:00-07:00,12144.310515939596
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 1990-06-24 09:00:00-07:00,45435.647605597595
 1990-06-24 10:00:00-07:00,54694.79251066385
 1990-06-24 11:00:00-07:00,59488.47218282443
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 1990-06-26 07:00:00-07:00,12048.764484157042
 1990-06-26 08:00:00-07:00,31076.700331300803
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 1990-06-26 11:00:00-07:00,59151.29308648961
 1990-06-26 12:00:00-07:00,59007.91402440691
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 1990-06-26 14:00:00-07:00,49881.593484841156
 1990-06-26 15:00:00-07:00,39696.19395192629
 1990-06-26 16:00:00-07:00,25816.954385583726
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 1990-06-27 05:00:00-07:00,937.3973499890488
 1990-06-27 06:00:00-07:00,661.6923259171183
 1990-06-27 07:00:00-07:00,11866.522838567302
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 1990-06-27 09:00:00-07:00,44819.95769098691
 1990-06-27 10:00:00-07:00,53505.27382809397
 1990-06-27 11:00:00-07:00,53078.1215986832
@@ -4283,13 +4283,13 @@ utc_time,0
 1990-06-28 09:00:00-07:00,44836.1632276809
 1990-06-28 10:00:00-07:00,53839.71757468955
 1990-06-28 11:00:00-07:00,56573.021059177045
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 1990-06-28 13:00:00-07:00,52737.63483742256
 1990-06-28 14:00:00-07:00,43469.258477198724
 1990-06-28 15:00:00-07:00,35111.02404620353
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 1990-06-28 17:00:00-07:00,10513.647785234374
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 1990-06-28 19:00:00-07:00,-1.884
 1990-06-28 20:00:00-07:00,-1.884
 1990-06-28 21:00:00-07:00,-1.884
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 1990-06-30 04:00:00-07:00,-1.884
 1990-06-30 05:00:00-07:00,1258.919856373223
 1990-06-30 06:00:00-07:00,5484.695094922203
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 1990-06-30 08:00:00-07:00,15966.645352518206
 1990-06-30 09:00:00-07:00,23412.7816268731
 1990-06-30 10:00:00-07:00,27725.943301691437
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 1990-06-30 15:00:00-07:00,28968.284962064958
 1990-06-30 16:00:00-07:00,21377.181369846192
 1990-06-30 17:00:00-07:00,10830.18258269344
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 1990-06-30 19:00:00-07:00,-1.884
 1990-06-30 20:00:00-07:00,-1.884
 1990-06-30 21:00:00-07:00,-1.884
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 1990-07-01 04:00:00-07:00,-1.884
 1990-07-01 05:00:00-07:00,-1.884
 1990-07-01 06:00:00-07:00,3059.1195082949075
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 1990-07-01 08:00:00-07:00,23025.988322529127
 1990-07-01 09:00:00-07:00,32717.917098641017
 1990-07-01 10:00:00-07:00,44708.854167369245
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 1990-07-01 13:00:00-07:00,55660.45939468336
 1990-07-01 14:00:00-07:00,47858.103385322705
 1990-07-01 15:00:00-07:00,31115.535806246437
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 1990-07-01 19:00:00-07:00,-1.884
 1990-07-01 20:00:00-07:00,-1.884
 1990-07-01 21:00:00-07:00,-1.884
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 1990-07-02 06:00:00-07:00,751.956339973546
 1990-07-02 07:00:00-07:00,11442.724268640784
 1990-07-02 08:00:00-07:00,30359.669315645366
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 1990-07-02 10:00:00-07:00,52942.29122750962
 1990-07-02 11:00:00-07:00,55678.66597704469
 1990-07-02 12:00:00-07:00,58586.34651078144
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 1990-07-03 05:00:00-07:00,-1.884
 1990-07-03 06:00:00-07:00,640.8384737136001
 1990-07-03 07:00:00-07:00,11505.231208136585
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 1990-07-03 09:00:00-07:00,44944.4094638089
 1990-07-03 10:00:00-07:00,53747.618961111
 1990-07-03 11:00:00-07:00,58305.827177603205
 1990-07-03 12:00:00-07:00,58188.137479836456
 1990-07-03 13:00:00-07:00,55522.16439364095
 1990-07-03 14:00:00-07:00,47662.14414475991
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 1990-07-03 16:00:00-07:00,22956.704278447825
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 1990-07-03 18:00:00-07:00,1686.4133096382357
 1990-07-03 19:00:00-07:00,-1.884
 1990-07-03 20:00:00-07:00,-1.884
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 1990-07-04 14:00:00-07:00,40789.72286778504
 1990-07-04 15:00:00-07:00,35190.57531299087
 1990-07-04 16:00:00-07:00,23816.79687420656
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 1990-07-04 18:00:00-07:00,2178.4485736690986
 1990-07-04 19:00:00-07:00,-1.884
 1990-07-04 20:00:00-07:00,-1.884
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 1990-07-05 07:00:00-07:00,11254.338045123102
 1990-07-05 08:00:00-07:00,29979.153378423413
 1990-07-05 09:00:00-07:00,43847.3405376688
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 1990-07-05 11:00:00-07:00,56606.04148812266
 1990-07-05 12:00:00-07:00,56764.69054733813
 1990-07-05 13:00:00-07:00,52595.69436956747
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 1990-07-06 04:00:00-07:00,-1.884
 1990-07-06 05:00:00-07:00,-1.884
 1990-07-06 06:00:00-07:00,696.9750330937164
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 1990-07-06 08:00:00-07:00,29725.919394731052
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 1990-07-06 10:00:00-07:00,52769.85232117983
 1990-07-06 11:00:00-07:00,57383.11396439239
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 1990-07-06 13:00:00-07:00,52990.34020367338
 1990-07-06 14:00:00-07:00,48870.62864461145
 1990-07-06 15:00:00-07:00,37876.43413943708
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 1990-07-07 14:00:00-07:00,47768.842400326015
 1990-07-07 15:00:00-07:00,36746.39632495702
 1990-07-07 16:00:00-07:00,19557.811093739012
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 1990-07-07 18:00:00-07:00,2495.055498124366
 1990-07-07 19:00:00-07:00,-1.884
 1990-07-07 20:00:00-07:00,-1.884
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 1990-07-08 04:00:00-07:00,-1.884
 1990-07-08 05:00:00-07:00,-1.884
 1990-07-08 06:00:00-07:00,687.7985624641783
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 1990-07-08 08:00:00-07:00,26456.174659457054
 1990-07-08 09:00:00-07:00,43113.95868512543
 1990-07-08 10:00:00-07:00,50020.04359126524
 1990-07-08 11:00:00-07:00,56689.58500939816
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 1990-07-08 13:00:00-07:00,42295.08243344256
 1990-07-08 14:00:00-07:00,30824.315362937446
 1990-07-08 15:00:00-07:00,22028.827267262084
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 1990-07-09 04:00:00-07:00,-1.884
 1990-07-09 05:00:00-07:00,-1.884
 1990-07-09 06:00:00-07:00,1214.371552489298
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 1990-07-09 08:00:00-07:00,29583.650345431564
 1990-07-09 09:00:00-07:00,43813.95362326468
 1990-07-09 10:00:00-07:00,52901.02592218684
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 1990-07-10 04:00:00-07:00,-1.884
 1990-07-10 05:00:00-07:00,-1.884
 1990-07-10 06:00:00-07:00,750.946995128382
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 1990-07-10 08:00:00-07:00,29798.859305981667
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 1990-07-10 10:00:00-07:00,48650.7365727318
 1990-07-10 11:00:00-07:00,54268.4363248229
 1990-07-10 12:00:00-07:00,55366.507263984
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 1990-07-11 06:00:00-07:00,708.7861366646423
 1990-07-11 07:00:00-07:00,10835.09234283338
 1990-07-11 08:00:00-07:00,29364.1011030794
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 1990-07-11 10:00:00-07:00,47358.968147918815
 1990-07-11 11:00:00-07:00,54782.40484724633
 1990-07-11 12:00:00-07:00,51972.101251526874
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 1990-07-12 05:00:00-07:00,-1.884
 1990-07-12 06:00:00-07:00,1099.693044835662
 1990-07-12 07:00:00-07:00,10613.362287691602
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 1990-07-12 09:00:00-07:00,43990.927389243065
 1990-07-12 10:00:00-07:00,51777.616892049584
 1990-07-12 11:00:00-07:00,58453.66644493275
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 1990-07-12 14:00:00-07:00,40997.545161552494
 1990-07-12 15:00:00-07:00,36722.401758404165
 1990-07-12 16:00:00-07:00,21199.15500741643
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 1990-07-12 19:00:00-07:00,-1.884
 1990-07-12 20:00:00-07:00,-1.884
 1990-07-12 21:00:00-07:00,-1.884
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 1990-07-13 05:00:00-07:00,-1.884
 1990-07-13 06:00:00-07:00,1699.0798901431851
 1990-07-13 07:00:00-07:00,11711.392577257395
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 1990-07-13 11:00:00-07:00,48091.48183173802
 1990-07-13 12:00:00-07:00,40019.80533069687
 1990-07-13 13:00:00-07:00,37756.74296917883
 1990-07-13 14:00:00-07:00,37867.656874699045
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 1990-07-13 16:00:00-07:00,21511.697992769656
 1990-07-13 17:00:00-07:00,9962.439837666832
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 1990-07-13 19:00:00-07:00,-1.884
 1990-07-13 20:00:00-07:00,-1.884
 1990-07-13 21:00:00-07:00,-1.884
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 1990-07-16 04:00:00-07:00,-1.884
 1990-07-16 05:00:00-07:00,-1.884
 1990-07-16 06:00:00-07:00,806.3513159682319
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 1990-07-16 08:00:00-07:00,29718.83139314444
 1990-07-16 09:00:00-07:00,44072.456550106086
 1990-07-16 10:00:00-07:00,52314.05320789842
 1990-07-16 11:00:00-07:00,55279.875386236454
 1990-07-16 12:00:00-07:00,50273.99230471418
 1990-07-16 13:00:00-07:00,38938.09726794528
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 1990-07-16 15:00:00-07:00,21910.48988093168
 1990-07-16 16:00:00-07:00,16950.527859496153
 1990-07-16 17:00:00-07:00,6575.147908250887
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 1990-07-17 04:00:00-07:00,-1.884
 1990-07-17 05:00:00-07:00,-1.884
 1990-07-17 06:00:00-07:00,825.8178856789642
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 1990-07-17 08:00:00-07:00,29024.229236280375
 1990-07-17 09:00:00-07:00,42924.23710873592
 1990-07-17 10:00:00-07:00,52759.54531752921
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 1990-07-18 04:00:00-07:00,-1.884
 1990-07-18 05:00:00-07:00,-1.884
 1990-07-18 06:00:00-07:00,778.7334701979312
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 1990-07-18 08:00:00-07:00,27875.029734760414
 1990-07-18 09:00:00-07:00,43304.944600473646
 1990-07-18 10:00:00-07:00,52053.23657670225
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 1990-07-19 04:00:00-07:00,-1.884
 1990-07-19 05:00:00-07:00,-1.884
 1990-07-19 06:00:00-07:00,616.7011658622398
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 1990-07-19 10:00:00-07:00,48963.33116787809
 1990-07-19 11:00:00-07:00,56296.953079662955
 1990-07-19 12:00:00-07:00,53149.51986367341
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 1990-07-19 15:00:00-07:00,37875.75075371891
 1990-07-19 16:00:00-07:00,23022.643789056678
 1990-07-19 17:00:00-07:00,9693.874348222129
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 1990-07-19 19:00:00-07:00,-1.884
 1990-07-19 20:00:00-07:00,-1.884
 1990-07-19 21:00:00-07:00,-1.884
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 1990-07-20 04:00:00-07:00,-1.884
 1990-07-20 05:00:00-07:00,-1.884
 1990-07-20 06:00:00-07:00,850.6155684004062
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 1990-07-20 08:00:00-07:00,29664.242802199627
 1990-07-20 09:00:00-07:00,42671.5298757459
 1990-07-20 10:00:00-07:00,50813.09733464556
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 1990-07-21 13:00:00-07:00,46044.19533985412
 1990-07-21 14:00:00-07:00,42225.73401536923
 1990-07-21 15:00:00-07:00,34444.02375383527
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 1990-07-21 19:00:00-07:00,-1.884
 1990-07-21 20:00:00-07:00,-1.884
 1990-07-21 21:00:00-07:00,-1.884
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 1990-07-22 04:00:00-07:00,-1.884
 1990-07-22 05:00:00-07:00,-1.884
 1990-07-22 06:00:00-07:00,693.5688207910442
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 1990-07-22 08:00:00-07:00,29333.98071869143
 1990-07-22 09:00:00-07:00,44058.55609468166
 1990-07-22 10:00:00-07:00,48965.52899542858
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 1990-07-22 13:00:00-07:00,52739.8959698934
 1990-07-22 14:00:00-07:00,47653.60695976891
 1990-07-22 15:00:00-07:00,36271.81775505936
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 1990-07-22 17:00:00-07:00,9166.160844185037
 1990-07-22 18:00:00-07:00,1534.0398858008543
 1990-07-22 19:00:00-07:00,-1.884
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 1990-07-23 05:00:00-07:00,-1.884
 1990-07-23 06:00:00-07:00,730.2083990369125
 1990-07-23 07:00:00-07:00,10911.280467848488
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 1990-07-23 09:00:00-07:00,44853.25883642799
 1990-07-23 10:00:00-07:00,53036.43650492924
 1990-07-23 11:00:00-07:00,48186.502503965545
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 1990-07-23 14:00:00-07:00,31894.90140802783
 1990-07-23 15:00:00-07:00,23130.454549939775
 1990-07-23 16:00:00-07:00,22444.70070179775
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 1990-07-23 19:00:00-07:00,-1.884
 1990-07-23 20:00:00-07:00,-1.884
 1990-07-23 21:00:00-07:00,-1.884
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 1990-07-24 04:00:00-07:00,-1.884
 1990-07-24 05:00:00-07:00,-1.884
 1990-07-24 06:00:00-07:00,2546.46042872371
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 1990-07-24 12:00:00-07:00,49175.45346719183
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 1990-07-24 16:00:00-07:00,18923.404534111905
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 1990-07-24 19:00:00-07:00,-1.884
 1990-07-24 20:00:00-07:00,-1.884
 1990-07-24 21:00:00-07:00,-1.884
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 1990-07-25 07:00:00-07:00,11221.026614262104
 1990-07-25 08:00:00-07:00,28857.86591324228
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 1990-07-25 11:00:00-07:00,54894.098101671625
 1990-07-25 12:00:00-07:00,49383.51198097911
 1990-07-25 13:00:00-07:00,46500.986071492625
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 1990-07-26 05:00:00-07:00,-1.884
 1990-07-26 06:00:00-07:00,1071.775586430415
 1990-07-26 07:00:00-07:00,10703.437546680878
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 1990-07-26 13:00:00-07:00,49414.895673258565
 1990-07-26 14:00:00-07:00,41823.610177674236
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 1990-07-27 04:00:00-07:00,-1.884
 1990-07-27 05:00:00-07:00,-1.884
 1990-07-27 06:00:00-07:00,1158.4473039973527
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 1990-07-27 10:00:00-07:00,47444.29568784725
 1990-07-27 11:00:00-07:00,42376.3859628489
 1990-07-27 12:00:00-07:00,50620.99685083017
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 1990-07-27 15:00:00-07:00,36650.17038260701
 1990-07-27 16:00:00-07:00,23017.034195711054
 1990-07-27 17:00:00-07:00,10037.767192612231
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 1990-07-27 19:00:00-07:00,-1.884
 1990-07-27 20:00:00-07:00,-1.884
 1990-07-27 21:00:00-07:00,-1.884
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 1990-07-28 04:00:00-07:00,-1.884
 1990-07-28 05:00:00-07:00,-1.884
 1990-07-28 06:00:00-07:00,3137.321670753463
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 1990-07-28 08:00:00-07:00,28422.819641444108
 1990-07-28 09:00:00-07:00,43415.48214201967
 1990-07-28 10:00:00-07:00,54225.60422903372
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 1990-07-29 04:00:00-07:00,-1.884
 1990-07-29 05:00:00-07:00,-1.884
 1990-07-29 06:00:00-07:00,425.6882786073721
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 1990-07-29 11:00:00-07:00,53243.961308244834
 1990-07-29 12:00:00-07:00,53207.4547808101
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 1990-07-29 15:00:00-07:00,23004.743797723382
 1990-07-29 16:00:00-07:00,10699.410617431808
 1990-07-29 17:00:00-07:00,6018.048764982464
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 1990-07-29 19:00:00-07:00,-1.884
 1990-07-29 20:00:00-07:00,-1.884
 1990-07-29 21:00:00-07:00,-1.884
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 1990-07-30 04:00:00-07:00,-1.884
 1990-07-30 05:00:00-07:00,-1.884
 1990-07-30 06:00:00-07:00,592.1520639451821
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 1990-07-30 10:00:00-07:00,53950.20242486379
 1990-07-30 11:00:00-07:00,53708.874158750164
 1990-07-30 12:00:00-07:00,56648.98032680446
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 1990-07-30 15:00:00-07:00,18524.279332692804
 1990-07-30 16:00:00-07:00,10523.534267887744
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 1990-07-31 06:00:00-07:00,1793.0180835003557
 1990-07-31 07:00:00-07:00,9640.94655476209
 1990-07-31 08:00:00-07:00,27150.83640858554
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 1990-07-31 10:00:00-07:00,52324.9836879302
 1990-07-31 11:00:00-07:00,54088.125609048686
 1990-07-31 12:00:00-07:00,46291.02592104641
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 1990-08-01 04:00:00-07:00,-1.884
 1990-08-01 05:00:00-07:00,-1.884
 1990-08-01 06:00:00-07:00,968.695203349465
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 1990-08-01 13:00:00-07:00,51286.61505841708
 1990-08-01 14:00:00-07:00,44581.451667171204
 1990-08-01 15:00:00-07:00,27940.96295546717
 1990-08-01 16:00:00-07:00,19241.200869864242
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 1990-08-01 19:00:00-07:00,-1.884
 1990-08-01 20:00:00-07:00,-1.884
 1990-08-01 21:00:00-07:00,-1.884
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 1990-08-02 13:00:00-07:00,56148.840488460584
 1990-08-02 14:00:00-07:00,50201.389178643156
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 1990-08-02 17:00:00-07:00,8154.813466964198
 1990-08-02 18:00:00-07:00,1394.8767139330132
 1990-08-02 19:00:00-07:00,-1.884
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 1990-08-03 05:00:00-07:00,-1.884
 1990-08-03 06:00:00-07:00,1363.0104877723138
 1990-08-03 07:00:00-07:00,11287.695052719591
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 1990-08-03 10:00:00-07:00,54478.86530301252
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 1990-08-03 15:00:00-07:00,39516.44620164418
 1990-08-03 16:00:00-07:00,26439.104787425247
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 1990-08-04 12:00:00-07:00,59438.093646951405
 1990-08-04 13:00:00-07:00,54385.57892781948
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 1990-08-04 17:00:00-07:00,9936.412629330922
 1990-08-04 18:00:00-07:00,990.2809638521475
 1990-08-04 19:00:00-07:00,-1.884
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 1990-08-05 04:00:00-07:00,-1.884
 1990-08-05 05:00:00-07:00,-1.884
 1990-08-05 06:00:00-07:00,174.04318473199552
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 1990-08-05 10:00:00-07:00,55065.58572411623
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 1990-08-05 19:00:00-07:00,-1.884
 1990-08-05 20:00:00-07:00,-1.884
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 1990-08-06 10:00:00-07:00,54465.51367641641
 1990-08-06 11:00:00-07:00,60243.311787159255
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 1990-08-06 15:00:00-07:00,38125.26574401844
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 1990-08-06 18:00:00-07:00,725.7909845479014
 1990-08-06 19:00:00-07:00,-1.884
 1990-08-06 20:00:00-07:00,-1.884
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 1990-08-07 05:00:00-07:00,-1.884
 1990-08-07 06:00:00-07:00,500.14868493154205
 1990-08-07 07:00:00-07:00,11355.147094534119
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 1990-08-07 10:00:00-07:00,45391.58699831889
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 1990-08-07 14:00:00-07:00,49459.983663529754
 1990-08-07 15:00:00-07:00,39025.372280984295
 1990-08-07 16:00:00-07:00,19967.10287196269
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 1990-08-07 19:00:00-07:00,-1.884
 1990-08-07 20:00:00-07:00,-1.884
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 1990-08-08 07:00:00-07:00,11519.577888170135
 1990-08-08 08:00:00-07:00,31591.30970396689
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 1990-08-08 13:00:00-07:00,53231.19442088632
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 1990-08-09 04:00:00-07:00,-1.884
 1990-08-09 05:00:00-07:00,-1.884
 1990-08-09 06:00:00-07:00,286.91043815852527
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 1990-08-09 10:00:00-07:00,57438.93923733335
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 1990-08-09 14:00:00-07:00,52260.9731783112
 1990-08-09 15:00:00-07:00,41441.97512059973
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 1990-08-09 19:00:00-07:00,-1.884
 1990-08-09 20:00:00-07:00,-1.884
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 1990-08-10 04:00:00-07:00,-1.884
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 1990-08-10 10:00:00-07:00,52496.410207860165
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 1990-08-10 19:00:00-07:00,-1.884
 1990-08-10 20:00:00-07:00,-1.884
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 1990-08-11 07:00:00-07:00,12700.34028879018
 1990-08-11 08:00:00-07:00,27057.750870076263
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 1990-08-11 12:00:00-07:00,60441.91813872365
 1990-08-11 13:00:00-07:00,56631.192681925706
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 1990-08-12 13:00:00-07:00,56466.89525072752
 1990-08-12 14:00:00-07:00,50658.37359694278
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 1990-08-12 20:00:00-07:00,-1.884
 1990-08-12 21:00:00-07:00,-1.884
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 1990-08-13 06:00:00-07:00,453.66605039514116
 1990-08-13 07:00:00-07:00,12148.145814313795
 1990-08-13 08:00:00-07:00,30548.530064866274
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 1990-08-13 10:00:00-07:00,51793.41649207468
 1990-08-13 11:00:00-07:00,53426.91437710642
 1990-08-13 12:00:00-07:00,51994.096640517586
 1990-08-13 13:00:00-07:00,54679.50230544208
 1990-08-13 14:00:00-07:00,44078.433079850336
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 1990-08-13 18:00:00-07:00,464.8791505177463
 1990-08-13 19:00:00-07:00,-1.884
 1990-08-13 20:00:00-07:00,-1.884
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 1990-08-14 06:00:00-07:00,599.1334648003399
 1990-08-14 07:00:00-07:00,11114.43838640038
 1990-08-14 08:00:00-07:00,17705.955594496347
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 1990-08-14 11:00:00-07:00,40801.59909698572
 1990-08-14 12:00:00-07:00,46679.27183460192
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 1990-08-15 04:00:00-07:00,-1.884
 1990-08-15 05:00:00-07:00,-1.884
 1990-08-15 06:00:00-07:00,675.8953647529645
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 1990-08-15 09:00:00-07:00,40923.96696873136
 1990-08-15 10:00:00-07:00,50495.457043631555
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 1990-08-15 14:00:00-07:00,48382.95102355744
 1990-08-15 15:00:00-07:00,32404.338326291356
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 1990-08-15 19:00:00-07:00,-1.884
 1990-08-15 20:00:00-07:00,-1.884
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 1990-08-16 19:00:00-07:00,-1.884
 1990-08-16 20:00:00-07:00,-1.884
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 1990-08-18 19:00:00-07:00,-1.884
 1990-08-18 20:00:00-07:00,-1.884
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 1990-08-19 20:00:00-07:00,-1.884
 1990-08-19 21:00:00-07:00,-1.884
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 1990-08-20 19:00:00-07:00,-1.884
 1990-08-20 20:00:00-07:00,-1.884
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 1990-08-21 20:00:00-07:00,-1.884
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 1990-08-23 19:00:00-07:00,-1.884
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 1990-08-24 06:00:00-07:00,666.5522971412296
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 1990-08-24 18:00:00-07:00,159.79330111743784
 1990-08-24 19:00:00-07:00,-1.884
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 1990-08-27 20:00:00-07:00,-1.884
 1990-08-27 21:00:00-07:00,-1.884
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 1990-08-28 16:00:00-07:00,16018.035837348323
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 1990-08-29 13:00:00-07:00,51736.10885915347
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 1990-08-29 18:00:00-07:00,-1.884
 1990-08-29 19:00:00-07:00,-1.884
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 1990-09-05 18:00:00-07:00,-1.884
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 1990-09-15 16:00:00-07:00,13603.948763761538
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 1990-09-16 06:00:00-07:00,1434.5908058709647
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 1990-09-16 18:00:00-07:00,-1.884
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 1990-09-19 05:00:00-07:00,-1.884
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 1990-09-21 18:00:00-07:00,-1.884
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 1990-09-22 18:00:00-07:00,-1.884
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 1990-09-24 19:00:00-07:00,-1.884
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 1990-09-25 18:00:00-07:00,-1.884
 1990-09-25 19:00:00-07:00,-1.884
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 1990-09-26 19:00:00-07:00,-1.884
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 1990-10-21 15:00:00-07:00,30923.264739625494
 1990-10-21 16:00:00-07:00,12304.010102759683
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 1990-10-23 05:00:00-07:00,-1.884
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 1990-10-24 18:00:00-07:00,-1.884
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 1990-10-26 17:00:00-07:00,-1.884
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 1990-11-10 17:00:00-07:00,-1.884
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 1990-11-13 17:00:00-07:00,-1.884
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 1990-11-30 19:00:00-07:00,-1.884
@@ -8024,14 +8024,14 @@ utc_time,0
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 1990-12-01 18:00:00-07:00,-1.884
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@@ -8050,7 +8050,7 @@ utc_time,0
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 1990-12-02 13:00:00-07:00,61738.80423600609
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@@ -8071,7 +8071,7 @@ utc_time,0
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 1990-12-03 06:00:00-07:00,-1.884
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 1990-12-03 10:00:00-07:00,67438.49812663435
 1990-12-03 11:00:00-07:00,71425.3447192949
@@ -8097,7 +8097,7 @@ utc_time,0
 1990-12-04 07:00:00-07:00,-1.884
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@@ -8122,12 +8122,12 @@ utc_time,0
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 1990-12-05 17:00:00-07:00,-1.884
 1990-12-05 18:00:00-07:00,-1.884
 1990-12-05 19:00:00-07:00,-1.884
@@ -8172,7 +8172,7 @@ utc_time,0
 1990-12-07 10:00:00-07:00,65306.94123909712
 1990-12-07 11:00:00-07:00,69225.45422225147
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 1990-12-07 15:00:00-07:00,28605.725394965626
 1990-12-07 16:00:00-07:00,6124.653469570145
@@ -8222,7 +8222,7 @@ utc_time,0
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 1990-12-09 13:00:00-07:00,59456.97485957716
 1990-12-09 14:00:00-07:00,46219.2818396814
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 1990-12-09 16:00:00-07:00,6008.1535045971605
 1990-12-09 17:00:00-07:00,-1.884
 1990-12-09 18:00:00-07:00,-1.884
@@ -8242,7 +8242,7 @@ utc_time,0
 1990-12-10 08:00:00-07:00,40887.48233868825
 1990-12-10 09:00:00-07:00,52644.384683830445
 1990-12-10 10:00:00-07:00,59804.57179364572
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 1990-12-10 12:00:00-07:00,61371.96102584878
 1990-12-10 13:00:00-07:00,56216.36736387249
 1990-12-10 14:00:00-07:00,41089.32561405093
@@ -8266,7 +8266,7 @@ utc_time,0
 1990-12-11 08:00:00-07:00,34501.89364240542
 1990-12-11 09:00:00-07:00,44707.20101078777
 1990-12-11 10:00:00-07:00,60552.93960295749
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 1990-12-11 12:00:00-07:00,45525.9947259202
 1990-12-11 13:00:00-07:00,33301.987255805885
 1990-12-11 14:00:00-07:00,27034.30496609023
@@ -8289,7 +8289,7 @@ utc_time,0
 1990-12-12 07:00:00-07:00,-1.884
 1990-12-12 08:00:00-07:00,44170.129967694986
 1990-12-12 09:00:00-07:00,55659.33548767052
-1990-12-12 10:00:00-07:00,64240.3822016438
+1990-12-12 10:00:00-07:00,64240.38220164377
 1990-12-12 11:00:00-07:00,68157.87754682094
 1990-12-12 12:00:00-07:00,66911.49353876189
 1990-12-12 13:00:00-07:00,60468.18148508126
@@ -8339,7 +8339,7 @@ utc_time,0
 1990-12-14 09:00:00-07:00,42149.687706319004
 1990-12-14 10:00:00-07:00,42454.29675309685
 1990-12-14 11:00:00-07:00,37939.283130961885
-1990-12-14 12:00:00-07:00,46612.25897602046
+1990-12-14 12:00:00-07:00,46612.25897602044
 1990-12-14 13:00:00-07:00,48540.24334947921
 1990-12-14 14:00:00-07:00,42895.44356676
 1990-12-14 15:00:00-07:00,28050.193464729437
@@ -8383,8 +8383,8 @@ utc_time,0
 1990-12-16 05:00:00-07:00,-1.884
 1990-12-16 06:00:00-07:00,-1.884
 1990-12-16 07:00:00-07:00,-1.884
-1990-12-16 08:00:00-07:00,42324.896739135474
-1990-12-16 09:00:00-07:00,53618.6050513543
+1990-12-16 08:00:00-07:00,42324.89673913544
+1990-12-16 09:00:00-07:00,53618.605051354316
 1990-12-16 10:00:00-07:00,61763.235051121956
 1990-12-16 11:00:00-07:00,63652.260644478985
 1990-12-16 12:00:00-07:00,59166.42883960527
@@ -8503,7 +8503,7 @@ utc_time,0
 1990-12-21 05:00:00-07:00,-1.884
 1990-12-21 06:00:00-07:00,-1.884
 1990-12-21 07:00:00-07:00,-1.884
-1990-12-21 08:00:00-07:00,45287.75064352843
+1990-12-21 08:00:00-07:00,45287.75064352842
 1990-12-21 09:00:00-07:00,57283.59356848589
 1990-12-21 10:00:00-07:00,66808.79495419654
 1990-12-21 11:00:00-07:00,70891.9872498991
@@ -8511,7 +8511,7 @@ utc_time,0
 1990-12-21 13:00:00-07:00,63869.31020331322
 1990-12-21 14:00:00-07:00,50472.6176332551
 1990-12-21 15:00:00-07:00,31666.394059434773
-1990-12-21 16:00:00-07:00,8168.321851458573
+1990-12-21 16:00:00-07:00,8168.321851458576
 1990-12-21 17:00:00-07:00,-1.884
 1990-12-21 18:00:00-07:00,-1.884
 1990-12-21 19:00:00-07:00,-1.884
@@ -8583,7 +8583,7 @@ utc_time,0
 1990-12-24 13:00:00-07:00,64637.3514294052
 1990-12-24 14:00:00-07:00,52726.50157067106
 1990-12-24 15:00:00-07:00,33465.7807579529
-1990-12-24 16:00:00-07:00,9073.90608759405
+1990-12-24 16:00:00-07:00,9073.906087594054
 1990-12-24 17:00:00-07:00,-1.884
 1990-12-24 18:00:00-07:00,-1.884
 1990-12-24 19:00:00-07:00,-1.884
@@ -8606,8 +8606,8 @@ utc_time,0
 1990-12-25 12:00:00-07:00,69513.35517058188
 1990-12-25 13:00:00-07:00,63591.69404673951
 1990-12-25 14:00:00-07:00,51474.73484499653
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-1990-12-25 16:00:00-07:00,8351.975582925155
+1990-12-25 15:00:00-07:00,32588.296325946303
+1990-12-25 16:00:00-07:00,8351.975582925154
 1990-12-25 17:00:00-07:00,-1.884
 1990-12-25 18:00:00-07:00,-1.884
 1990-12-25 19:00:00-07:00,-1.884
@@ -8630,7 +8630,7 @@ utc_time,0
 1990-12-26 12:00:00-07:00,66542.84824658415
 1990-12-26 13:00:00-07:00,60908.75005325336
 1990-12-26 14:00:00-07:00,49170.49640198754
-1990-12-26 15:00:00-07:00,31752.360066526704
+1990-12-26 15:00:00-07:00,31752.36006652672
 1990-12-26 16:00:00-07:00,8919.362503954457
 1990-12-26 17:00:00-07:00,-1.884
 1990-12-26 18:00:00-07:00,-1.884
@@ -8671,7 +8671,7 @@ utc_time,0
 1990-12-28 05:00:00-07:00,-1.884
 1990-12-28 06:00:00-07:00,-1.884
 1990-12-28 07:00:00-07:00,-1.884
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 1990-12-28 09:00:00-07:00,24357.35470068189
 1990-12-28 10:00:00-07:00,30136.70621363226
 1990-12-28 11:00:00-07:00,13739.427697581083
@@ -8679,7 +8679,7 @@ utc_time,0
 1990-12-28 13:00:00-07:00,22962.244796583407
 1990-12-28 14:00:00-07:00,30067.492106418696
 1990-12-28 15:00:00-07:00,19065.936697705667
-1990-12-28 16:00:00-07:00,5165.933317641082
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 1990-12-28 17:00:00-07:00,-1.884
 1990-12-28 18:00:00-07:00,-1.884
 1990-12-28 19:00:00-07:00,-1.884
@@ -8720,7 +8720,7 @@ utc_time,0
 1990-12-30 06:00:00-07:00,-1.884
 1990-12-30 07:00:00-07:00,-1.884
 1990-12-30 08:00:00-07:00,7696.5808141909865
-1990-12-30 09:00:00-07:00,26934.49846071119
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 1990-12-30 10:00:00-07:00,27344.3549753615
 1990-12-30 11:00:00-07:00,24664.19174609311
 1990-12-30 12:00:00-07:00,21055.94351142627
@@ -8744,7 +8744,7 @@ utc_time,0
 1990-12-31 06:00:00-07:00,-1.884
 1990-12-31 07:00:00-07:00,-1.884
 1990-12-31 08:00:00-07:00,33206.39073888092
-1990-12-31 09:00:00-07:00,51397.4036105359
+1990-12-31 09:00:00-07:00,51397.403610535854
 1990-12-31 10:00:00-07:00,61810.99041657732
 1990-12-31 11:00:00-07:00,71263.08718663313
 1990-12-31 12:00:00-07:00,71653.03787358473
diff --git a/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_battery_example.ipynb b/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_battery_example.ipynb
index 43b8f22..36744e4 100644
--- a/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_battery_example.ipynb
+++ b/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_battery_example.ipynb
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "2528b10c-e8f0-44b1-8dba-8900f9a43dcd",
    "metadata": {},
    "outputs": [
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "49ae96f2-c97b-4c46-8a67-e2d67cf99968",
    "metadata": {},
    "outputs": [],
@@ -93,7 +93,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "51190348-fe4a-4bb2-bca8-d7a0d5b1d949",
    "metadata": {},
    "outputs": [
@@ -190,7 +190,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "id": "c5552346-3fe3-41f4-befa-f9d96fee11fe",
    "metadata": {},
    "outputs": [
@@ -198,7 +198,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "7.0.0\n"
+      "7.1.0\n"
      ]
     }
    ],
@@ -242,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "id": "13884504-bb6e-47a2-b7f4-27e2126b4c23",
    "metadata": {},
    "outputs": [],
@@ -269,7 +269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "id": "76349013",
    "metadata": {},
    "outputs": [],
@@ -284,7 +284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "id": "edf2f304",
    "metadata": {},
    "outputs": [],
@@ -305,7 +305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "id": "e0b193a8-d4e1-49df-a07e-4fefb968c306",
    "metadata": {},
    "outputs": [],
@@ -327,7 +327,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "id": "018f39c3",
    "metadata": {},
    "outputs": [
@@ -337,7 +337,7 @@
        "Text(0, 0.5, 'Power (kW)')"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -360,17 +360,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "id": "218148cf",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1fb77396870>"
+       "<matplotlib.legend.Legend at 0x31c562f00>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -396,7 +396,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "id": "35fba3de",
    "metadata": {},
    "outputs": [
@@ -406,7 +406,7 @@
        "Text(0, 0.5, 'Battery SOC (%)')"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -429,7 +429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 12,
    "id": "f1421596",
    "metadata": {},
    "outputs": [
@@ -439,7 +439,7 @@
        "Text(0, 0.5, 'Battery capacity as percent of nameplate (%)')"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -463,7 +463,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pysam-pvlib",
+   "display_name": "pysam_build_3.12",
    "language": "python",
    "name": "python3"
   },
@@ -477,7 +477,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_example.ipynb b/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_example.ipynb
index b6c4eea..c348e41 100644
--- a/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_example.ipynb
+++ b/Examples/PVPMC_pvlib_PySAM_example/pvlib_pysam_example.ipynb
@@ -90,7 +90,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Salt Lake City    2.262303e+06\n",
+      "Salt Lake City    2.264885e+06\n",
       "dtype: float64\n",
       "utc_time\n",
       "2016-01-01 00:00:00+00:00      -300.391800\n",
@@ -99,11 +99,11 @@
       "2016-01-01 03:00:00+00:00      -300.391800\n",
       "2016-01-01 04:00:00+00:00      -300.391800\n",
       "                                 ...      \n",
-      "2021-12-31 19:00:00+00:00    757522.036621\n",
-      "2021-12-31 20:00:00+00:00    819302.834632\n",
-      "2021-12-31 21:00:00+00:00    674898.047547\n",
-      "2021-12-31 22:00:00+00:00    417112.003799\n",
-      "2021-12-31 23:00:00+00:00    163022.404209\n",
+      "2021-12-31 19:00:00+00:00    748030.045143\n",
+      "2021-12-31 20:00:00+00:00    809147.408402\n",
+      "2021-12-31 21:00:00+00:00    663100.887084\n",
+      "2021-12-31 22:00:00+00:00    405310.075774\n",
+      "2021-12-31 23:00:00+00:00    156381.264208\n",
       "Length: 8760, dtype: float64\n"
      ]
     },
@@ -119,7 +119,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -3444,9 +3444,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Net Present Value:  166395.09267949825\n",
-      "Internal Rate of Return:  12.4859484035122\n",
-      "Levelized cost of energy (nominal):  4.121248389398984  cents/kWh\n"
+      "Net Present Value:  168166.65386211465\n",
+      "Internal Rate of Return:  12.543195066701099\n",
+      "Levelized cost of energy (nominal):  4.115317813808767  cents/kWh\n"
      ]
     },
     {
@@ -3461,7 +3461,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -3484,7 +3484,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pysam_build_3.10",
+   "display_name": "pysam_build_3.12",
    "language": "python",
    "name": "python3"
   },
@@ -3498,7 +3498,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/Examples/PVsamv1Tools.ipynb b/Examples/PVsamv1Tools.ipynb
index dee0344..73cb9fa 100644
--- a/Examples/PVsamv1Tools.ipynb
+++ b/Examples/PVsamv1Tools.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "876a747c-744c-4b6d-b464-d8caeec98c5a",
    "metadata": {},
    "outputs": [
@@ -20,7 +20,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "7.0.0\n"
+      "7.1.0\n"
      ]
     }
    ],
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "0ea67d44",
    "metadata": {},
    "outputs": [
@@ -56,11 +56,7 @@
      "text": [
       "\n",
       "Starting data download for solar using 1 thread workers.\n",
-      "Getting list of available NSRDB files for 39.7, -105.1.\n",
-      "List of available data saved to ./nsrdb_data_query_response_39.7_-105.1.json.\n",
-      "https://developer.nrel.gov/api/nsrdb/v2/solar/psm3-tmy-download.csv?names=tmy&wkt=POINT%28-105.1+39.7%29&interval=60&api_key=DEMO_KEY&email=test_email@email.org&utc=false\n",
-      "Downloading file.\n",
-      "Success! File downloaded to ./nsrdb_39.7_-105.1_psm3-tmy_60_tmy.csv.\n",
+      "File already exists. Skipping download: ./nsrdb_39.7_-105.1_psm3-tmy_60_tmy.csv\n",
       "./nsrdb_39.7_-105.1_psm3-tmy_60_tmy.csv\n"
      ]
     }
@@ -87,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "2ac0484b-5598-42f9-b0df-cb525326b62d",
    "metadata": {},
    "outputs": [
@@ -121,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "0b92e5d7-f5fc-4bcb-a2f9-6fe04fada66f",
    "metadata": {},
    "outputs": [
@@ -165,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "797a492b-29f1-4117-9953-c30bf8b52120",
    "metadata": {},
    "outputs": [
@@ -202,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "69a5ab17-f219-4364-9c6d-4c39eb83aa02",
    "metadata": {},
    "outputs": [
@@ -233,7 +229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "55d386d3-1de4-4b73-9f22-ee9cd93d5ae8",
    "metadata": {},
    "outputs": [
diff --git a/Examples/PySAMWorkshop.ipynb b/Examples/PySAMWorkshop.ipynb
index 5e50489..965e8d8 100644
--- a/Examples/PySAMWorkshop.ipynb
+++ b/Examples/PySAMWorkshop.ipynb
@@ -13,7 +13,7 @@
     "\n",
     "https://sam.nrel.gov/software-development-kit-sdk/pysam.html\n",
     "\n",
-    "Edit: Most recently tested with Version 7.0.0"
+    "Edit: Most recently tested with Version 7.10"
    ]
   },
   {
@@ -134,59 +134,59 @@
       "\n",
       "default(...)\n",
       "    default(config) -> Pvwattsv8\n",
-      "\n",
+      "    \n",
       "    Load defaults for the configuration ``config``. Available configurations are:\n",
-      "\n",
+      "    \n",
       "                    - *\"CustomGenerationPVWattsWindFuelCellBatteryHybridHostDeveloper\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"CustomGenerationPVWattsWindFuelCellBatteryHybridSingleOwner\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"FuelCellCommercial\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"FuelCellSingleOwner\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsBatteryCommercial\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsBatteryHostDeveloper\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsBatteryResidential\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsBatteryThirdParty\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsWindBatteryHybridHostDeveloper\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsWindBatteryHybridSingleOwner\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsWindFuelCellBatteryHybridHostDeveloper\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsWindFuelCellBatteryHybridSingleOwner\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsAllEquityPartnershipFlip\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsCommercial\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsCommunitySolar\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsHostDeveloper\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsLCOECalculator\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsLeveragedPartnershipFlip\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsMerchantPlant\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsNone\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsResidential\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsSaleLeaseback\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsSingleOwner\"*\n",
-      "\n",
+      "    \n",
       "                    - *\"PVWattsThirdParty\"*\n",
-      "\n",
+      "    \n",
       "    .. note::\n",
-      "\n",
+      "    \n",
       "            Some inputs do not have default values and may be assigned a value from the variable's **Required** attribute. See variable attribute descriptions below.\n",
       "\n"
      ]
@@ -244,11 +244,7 @@
        "  'shading_mxh': ((0.0,),),\n",
        "  'shading_string_option': 0.0,\n",
        "  'shading_timestep': ((0.0,),)},\n",
-       " 'AdjustmentFactors': {'adjust_constant': 0.0,\n",
-       "  'adjust_en_periods': 0.0,\n",
-       "  'adjust_en_timeindex': 0.0,\n",
-       "  'adjust_periods': ((0.0, 0.0, 0.0),),\n",
-       "  'adjust_timeindex': (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)},\n",
+       " 'AdjustmentFactors': {},\n",
        " 'HybridCosts': {},\n",
        " 'Outputs': {}}"
       ]
@@ -466,7 +462,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "7.0.0\n"
+      "6.0.1\n"
      ]
     }
    ],
@@ -530,15 +526,15 @@
      "output_type": "stream",
      "text": [
       "batt_kw\tbatt_kwh\tavg_npv\n",
-      "10\t40\t-147473.65633643177\n",
-      "20\t80\t-145960.27700371345\n",
-      "30\t120\t-144348.78036862888\n",
-      "40\t160\t-142720.9237405408\n",
-      "50\t200\t-141223.67201064204\n",
-      "60\t240\t-139892.3043450741\n",
-      "70\t280\t-138795.76235376217\n",
-      "80\t320\t-137730.97718782522\n",
-      "90\t360\t-136833.80261780682\n"
+      "10\t40\t-147282.62802741112\n",
+      "20\t80\t-145571.75869861347\n",
+      "30\t120\t-143772.44380822402\n",
+      "40\t160\t-142048.65461913403\n",
+      "50\t200\t-140455.99081696098\n",
+      "60\t240\t-139157.33053290664\n",
+      "70\t280\t-137966.71685081776\n",
+      "80\t320\t-136942.25426736692\n",
+      "90\t360\t-136015.89108209618\n"
      ]
     }
    ],
@@ -573,7 +569,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pysam_build_3.12",
+   "display_name": "pysam_build_3.8",
    "language": "python",
    "name": "python3"
   },
@@ -587,7 +583,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.0"
+   "version": "3.8.17"
   }
  },
  "nbformat": 4,
diff --git a/Examples/ResidentialPVBatteryWithCustomDispatch.py b/Examples/ResidentialPVBatteryWithCustomDispatch.py
index 5c19a04..855c293 100644
--- a/Examples/ResidentialPVBatteryWithCustomDispatch.py
+++ b/Examples/ResidentialPVBatteryWithCustomDispatch.py
@@ -8,7 +8,7 @@
 * PV: https://nrel-pysam.readthedocs.io/en/master/modules/Pvsamv1.html
 * Battery: https://nrel-pysam.readthedocs.io/en/master/modules/Battery.html
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 
 @author: brtietz
 """
diff --git a/Examples/SAMsimPVWattsCommercialExample.py b/Examples/SAMsimPVWattsCommercialExample.py
index 9e361fb..e554e9c 100755
--- a/Examples/SAMsimPVWattsCommercialExample.py
+++ b/Examples/SAMsimPVWattsCommercialExample.py
@@ -13,7 +13,7 @@
     Run the simulations.
     Print the results.
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 
 @author: frohro
 """
@@ -38,7 +38,7 @@
 # in the added simulation case.  Choose "JSON for inputs" and a .json file
 # with the title of your simulation case will be created where you select with
 # the "Open" button on the file dialog.
-json_file_path = 'Examples/100kW_PVWatts.json'  # Change this file name to yours!
+json_file_path = Path(__file__).parent / '100kW_PVWatts.json'  # Change this file name to yours!
 with open(json_file_path) as f:
         dic = json.load(f)
 # The next seven lines are needed to load the PySAM data structures with the
diff --git a/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb b/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb
index e74ff64..798e4b1 100644
--- a/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb	
+++ b/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb	
@@ -72,7 +72,7 @@
     {
      "data": {
       "text/plain": [
-       "'6.0.0'"
+       "'7.1.0'"
       ]
      },
      "execution_count": 3,
@@ -4136,11 +4136,16 @@
        "  'load_escalation': (0.0,)},\n",
        " 'PVLosses': {'enable_subhourly_clipping': 0.0,\n",
        "  'enable_subinterval_distribution': 0.0},\n",
-       " 'AdjustmentFactors': {'constant': 0.0,\n",
-       "  'en_periods': 0.0,\n",
-       "  'en_timeindex': 0.0,\n",
-       "  'periods': ((0.0, 0.0, 0.0),),\n",
-       "  'timeindex': (0.0,)},\n",
+       " 'AdjustmentFactors': {'adjust_constant': 0.0,\n",
+       "  'adjust_en_periods': 0.0,\n",
+       "  'adjust_en_timeindex': 0.0,\n",
+       "  'adjust_periods': ((0.0, 0.0, 0.0),),\n",
+       "  'adjust_timeindex': (0.0,),\n",
+       "  'dc_adjust_constant': 0.0,\n",
+       "  'dc_adjust_en_periods': 0.0,\n",
+       "  'dc_adjust_en_timeindex': 0.0,\n",
+       "  'dc_adjust_periods': ((0.0, 0.0, 0.0),),\n",
+       "  'dc_adjust_timeindex': (0.0,)},\n",
        " 'BatteryCell': {},\n",
        " 'BatteryDispatch': {},\n",
        " 'SystemCosts': {'om_production_escal': 0.0},\n",
@@ -9090,7 +9095,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/2089502906.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/2089502906.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  masterdate = mymod['Date'][0]\n"
      ]
     }
@@ -9109,7 +9114,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3381241117.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3381241117.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  otherbranchdate = mymod['Date'][0]\n"
      ]
     }
@@ -9202,43 +9207,43 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_a_ref = float(mymod.a_ref[0]) # 1.885731\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_adjust = float(mymod.Adjust[0]) # 10.400029\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_alpha_sc = float(mymod.alpha_sc[0]) # 0.004675\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_area = float(mymod.A_c[0]) # 1.979\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:6: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:6: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_beta_oc = float(mymod.beta_oc[0]) # -0.139925\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_gamma_r = float(mymod.gamma_r[0]) # -0.4028\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:8: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:8: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_i_l_ref = float(mymod.I_L_ref[0]) # 9.80468\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_i_mp_ref = float(mymod.I_mp_ref[0]) # 9.26\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:10: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:10: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_i_o_ref = float(mymod.I_o_ref[0]) # 7.72903e-11       # NOT THE SAME, DB says \"0.0\"\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:11: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:11: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_i_sc_ref = float(mymod.I_sc_ref[0]) # 9.8\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:12: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:12: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_is_bifacial = int(mymod.Bifacial[0]) # 1\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:13: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:13: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_module_length = float(mymod.Length[0]) # 2.011\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:14: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:14: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_module_width = float(mymod.Width[0]) # 0.984\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:18: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:18: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_n_s = float(mymod.N_s[0]) # 72\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:19: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:19: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_r_s = float(mymod.R_s[0]) #0.396799\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:20: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:20: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_r_sh_ref = float(mymod.R_sh_ref[0]) # 830.975492\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:21: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:21: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_t_noct = float(mymod.T_NOCT[0]) # 47.4\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:22: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:22: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_v_mp_ref = float(mymod.V_mp_ref[0]) # 38.9\n",
-      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_57231/3652071070.py:23: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "/var/folders/yh/xvlf1svn0xq6r2l4hzsggz2xt3qfdr/T/ipykernel_35906/3652071070.py:23: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "  cec_v_oc_ref = float(mymod.V_oc_ref[0]) # 48.2\n"
      ]
     }
@@ -9292,7 +9297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 22,
    "id": "c0a5c496",
    "metadata": {},
    "outputs": [],
@@ -9347,7 +9352,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 23,
    "id": "3fffb682",
    "metadata": {},
    "outputs": [],
@@ -9368,7 +9373,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 24,
    "id": "c96dab31",
    "metadata": {},
    "outputs": [
@@ -9488,7 +9493,7 @@
        "Fronius International GmbH: Fronius Symo 10.0-3...  3/1/2019          N  "
       ]
      },
-     "execution_count": 26,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -9501,7 +9506,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 25,
    "id": "bf2ee70e",
    "metadata": {},
    "outputs": [],
@@ -9531,7 +9536,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 26,
    "id": "61ddd7e0",
    "metadata": {},
    "outputs": [],
@@ -9550,7 +9555,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 27,
    "id": "06a89af6",
    "metadata": {},
    "outputs": [],
@@ -9629,7 +9634,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 28,
    "id": "728a923a",
    "metadata": {},
    "outputs": [],
@@ -9667,7 +9672,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 29,
    "id": "a168d4a0",
    "metadata": {},
    "outputs": [],
@@ -9677,7 +9682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 30,
    "id": "7c3a2fd2",
    "metadata": {},
    "outputs": [],
@@ -9700,7 +9705,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 31,
    "id": "d4a387d5",
    "metadata": {},
    "outputs": [],
@@ -9738,7 +9743,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 32,
    "id": "12639039",
    "metadata": {},
    "outputs": [],
@@ -9753,7 +9758,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 33,
    "id": "e50dbb64",
    "metadata": {},
    "outputs": [],
@@ -9775,7 +9780,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 34,
    "id": "8b44af3d",
    "metadata": {},
    "outputs": [
@@ -10019,17719 +10024,8961 @@
        "    <tr>\n",
        "      <th>2020-01-01 23:00:00</th>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.052115</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.2</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                         Grear      Gfront  DCP (kW)         DNI         DHI  \\\n",
-       "2020-01-01 00:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
-       "2020-01-01 01:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
-       "2020-01-01 02:00:00   0.000000    0.000000  0.000000    0.000000    0.006899   \n",
-       "2020-01-01 03:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
-       "2020-01-01 04:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
-       "2020-01-01 05:00:00   0.000000    0.000000  0.000000    0.000000    0.007147   \n",
-       "2020-01-01 06:00:00   0.000000    0.000000  0.000000    0.224083    0.000000   \n",
-       "2020-01-01 07:00:00   0.952828   10.864534  0.011111   29.900648    9.146110   \n",
-       "2020-01-01 08:00:00   5.280836   62.891234  0.072767   39.650845   45.072811   \n",
-       "2020-01-01 09:00:00  25.020240  424.175198  0.487038  488.902252   92.055008   \n",
-       "2020-01-01 10:00:00  22.112267  140.597987  0.170311   40.219421  139.379303   \n",
-       "2020-01-01 11:00:00  15.243913  136.514177  0.159731    1.458432  146.268784   \n",
-       "2020-01-01 12:00:00  15.045047  138.871464  0.162195    7.297924  143.908936   \n",
-       "2020-01-01 13:00:00  32.694059  421.791129  0.485976  514.294067  142.040833   \n",
-       "2020-01-01 14:00:00  28.891263  547.687319  0.626409  695.355957   87.838135   \n",
-       "2020-01-01 15:00:00   5.155149  454.184026  0.503649  704.084229   39.767941   \n",
-       "2020-01-01 16:00:00   1.067853   23.427810  0.023300   64.097702   13.479426   \n",
-       "2020-01-01 17:00:00   0.000000    0.000000  0.000000    0.118982    0.056990   \n",
-       "2020-01-01 18:00:00   0.000000    0.000000  0.000000    0.074463    0.000000   \n",
-       "2020-01-01 19:00:00   0.000000    0.000000  0.000000    0.040330    0.011045   \n",
-       "2020-01-01 20:00:00   0.000000    0.000000  0.000000    0.000000    0.001485   \n",
-       "2020-01-01 21:00:00   0.000000    0.000000  0.000000    0.063725    0.000000   \n",
-       "2020-01-01 22:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
-       "2020-01-01 23:00:00   0.000000    0.000000  0.000000    0.052115    0.000000   \n",
-       "\n",
-       "                     alb  \n",
-       "2020-01-01 00:00:00  0.2  \n",
-       "2020-01-01 01:00:00  0.2  \n",
-       "2020-01-01 02:00:00  0.2  \n",
-       "2020-01-01 03:00:00  0.2  \n",
-       "2020-01-01 04:00:00  0.2  \n",
-       "2020-01-01 05:00:00  0.2  \n",
-       "2020-01-01 06:00:00  0.2  \n",
-       "2020-01-01 07:00:00  0.2  \n",
-       "2020-01-01 08:00:00  0.2  \n",
-       "2020-01-01 09:00:00  0.2  \n",
-       "2020-01-01 10:00:00  0.2  \n",
-       "2020-01-01 11:00:00  0.2  \n",
-       "2020-01-01 12:00:00  0.2  \n",
-       "2020-01-01 13:00:00  0.2  \n",
-       "2020-01-01 14:00:00  0.2  \n",
-       "2020-01-01 15:00:00  0.2  \n",
-       "2020-01-01 16:00:00  0.2  \n",
-       "2020-01-01 17:00:00  0.2  \n",
-       "2020-01-01 18:00:00  0.2  \n",
-       "2020-01-01 19:00:00  0.2  \n",
-       "2020-01-01 20:00:00  0.2  \n",
-       "2020-01-01 21:00:00  0.2  \n",
-       "2020-01-01 22:00:00  0.2  \n",
-       "2020-01-01 23:00:00  0.2  "
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "weatherfile = pd.read_csv(solar_resource_file, skiprows=2)\n",
-    "timestamps = pd.to_datetime(weatherfile[['Year','Month','Day','Hour']])\n",
-    "df.index = timestamps\n",
-    "#df=df.rename_axis(\"index\")\n",
-    "df.head(24)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "id": "deb3ee05",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import plotly.express as px\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "id": "4c0cdea0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "startdate = '2020-11-06 0:0:0'\n",
-    "enddate = '2020-11-06 23:0:0'\n",
-    "\n",
-    "mybirthday = df[(df.index>startdate) & (df.index<enddate)]\n",
-    "\n",
-    "fig, ax = plt.subplots()\n",
-    "plt.plot(mybirthday.DNI, label='DNI')\n",
-    "plt.plot(mybirthday.Gfront, label='Front')\n",
-    "plt.plot(mybirthday.Grear, label='Rear')\n",
-    "plt.ylabel(\"Irradiance [W/m$^2$]\")\n",
-    "plt.legend()\n",
-    "fig.autofmt_xdate()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "id": "eb96c79f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "startdate = '2020-11-08 0:0:0'\n",
-    "enddate = '2020-11-08 23:0:0'\n",
-    "\n",
-    "mybirthday = df[(df.index>startdate) & (df.index<enddate)]\n",
-    "\n",
-    "fig, ax = plt.subplots()\n",
-    "plt.plot(mybirthday.DNI, label='DNI')\n",
-    "plt.plot(mybirthday.Gfront, label='Front')\n",
-    "plt.plot(mybirthday.Grear, label='Rear')\n",
-    "plt.ylabel(\"Irradiance [W/m$^2$]\")\n",
-    "plt.legend()\n",
-    "fig.autofmt_xdate()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "c9ae8080",
-   "metadata": {},
-   "source": [
-    "We can also explore with plotly any of the columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "id": "4a203939",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.plotly.v1+json": {
-       "config": {
-        "plotlyServerURL": "https://plot.ly"
-       },
-       "data": [
-        {
-         "hovertemplate": "variable=DCP (kW)<br>index=%{x}<br>value=%{y}<extra></extra>",
-         "legendgroup": "DCP (kW)",
-         "line": {
-          "color": "#636efa",
-          "dash": "solid"
-         },
-         "marker": {
-          "symbol": "circle"
-         },
-         "mode": "lines",
-         "name": "DCP (kW)",
-         "showlegend": true,
-         "type": "scattergl",
-         "x": [
-          "2020-01-01T00:00:00",
-          "2020-01-01T01:00:00",
-          "2020-01-01T02:00:00",
-          "2020-01-01T03:00:00",
-          "2020-01-01T04:00:00",
-          "2020-01-01T05:00:00",
-          "2020-01-01T06:00:00",
-          "2020-01-01T07:00:00",
-          "2020-01-01T08:00:00",
-          "2020-01-01T09:00:00",
-          "2020-01-01T10:00:00",
-          "2020-01-01T11:00:00",
-          "2020-01-01T12:00:00",
-          "2020-01-01T13:00:00",
-          "2020-01-01T14:00:00",
-          "2020-01-01T15:00:00",
-          "2020-01-01T16:00:00",
-          "2020-01-01T17:00:00",
-          "2020-01-01T18:00:00",
-          "2020-01-01T19:00:00",
-          "2020-01-01T20:00:00",
-          "2020-01-01T21:00:00",
-          "2020-01-01T22:00:00",
-          "2020-01-01T23:00:00",
-          "2020-01-02T00:00:00",
-          "2020-01-02T01:00:00",
-          "2020-01-02T02:00:00",
-          "2020-01-02T03:00:00",
-          "2020-01-02T04:00:00",
-          "2020-01-02T05:00:00",
-          "2020-01-02T06:00:00",
-          "2020-01-02T07:00:00",
-          "2020-01-02T08:00:00",
-          "2020-01-02T09:00:00",
-          "2020-01-02T10:00:00",
-          "2020-01-02T11:00:00",
-          "2020-01-02T12:00:00",
-          "2020-01-02T13:00:00",
-          "2020-01-02T14:00:00",
-          "2020-01-02T15:00:00",
-          "2020-01-02T16:00:00",
-          "2020-01-02T17:00:00",
-          "2020-01-02T18:00:00",
-          "2020-01-02T19:00:00",
-          "2020-01-02T20:00:00",
-          "2020-01-02T21:00:00",
-          "2020-01-02T22:00:00",
-          "2020-01-02T23:00:00",
-          "2020-01-03T00:00:00",
-          "2020-01-03T01:00:00",
-          "2020-01-03T02:00:00",
-          "2020-01-03T03:00:00",
-          "2020-01-03T04:00:00",
-          "2020-01-03T05:00:00",
-          "2020-01-03T06:00:00",
-          "2020-01-03T07:00:00",
-          "2020-01-03T08:00:00",
-          "2020-01-03T09:00:00",
-          "2020-01-03T10:00:00",
-          "2020-01-03T11:00:00",
-          "2020-01-03T12:00:00",
-          "2020-01-03T13:00:00",
-          "2020-01-03T14:00:00",
-          "2020-01-03T15:00:00",
-          "2020-01-03T16:00:00",
-          "2020-01-03T17:00:00",
-          "2020-01-03T18:00:00",
-          "2020-01-03T19:00:00",
-          "2020-01-03T20:00:00",
-          "2020-01-03T21:00:00",
-          "2020-01-03T22:00:00",
-          "2020-01-03T23:00:00",
-          "2020-01-04T00:00:00",
-          "2020-01-04T01:00:00",
-          "2020-01-04T02:00:00",
-          "2020-01-04T03:00:00",
-          "2020-01-04T04:00:00",
-          "2020-01-04T05:00:00",
-          "2020-01-04T06:00:00",
-          "2020-01-04T07:00:00",
-          "2020-01-04T08:00:00",
-          "2020-01-04T09:00:00",
-          "2020-01-04T10:00:00",
-          "2020-01-04T11:00:00",
-          "2020-01-04T12:00:00",
-          "2020-01-04T13:00:00",
-          "2020-01-04T14:00:00",
-          "2020-01-04T15:00:00",
-          "2020-01-04T16:00:00",
-          "2020-01-04T17:00:00",
-          "2020-01-04T18:00:00",
-          "2020-01-04T19:00:00",
-          "2020-01-04T20:00:00",
-          "2020-01-04T21:00:00",
-          "2020-01-04T22:00:00",
-          "2020-01-04T23:00:00",
-          "2020-01-05T00:00:00",
-          "2020-01-05T01:00:00",
-          "2020-01-05T02:00:00",
-          "2020-01-05T03:00:00",
-          "2020-01-05T04:00:00",
-          "2020-01-05T05:00:00",
-          "2020-01-05T06:00:00",
-          "2020-01-05T07:00:00",
-          "2020-01-05T08:00:00",
-          "2020-01-05T09:00:00",
-          "2020-01-05T10:00:00",
-          "2020-01-05T11:00:00",
-          "2020-01-05T12:00:00",
-          "2020-01-05T13:00:00",
-          "2020-01-05T14:00:00",
-          "2020-01-05T15:00:00",
-          "2020-01-05T16:00:00",
-          "2020-01-05T17:00:00",
-          "2020-01-05T18:00:00",
-          "2020-01-05T19:00:00",
-          "2020-01-05T20:00:00",
-          "2020-01-05T21:00:00",
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-          0.7121041218652258,
-          0.6741759374179663,
-          0.6049596123981212,
-          0.5980922191391992,
-          0.6677978824831762,
-          0.7310676041352944,
-          0.5518623054388424,
-          0.05562484719188777,
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-          0.3485981098905844,
-          0.6856450036981321,
-          0.651736898110581,
-          0.5886284631244173,
-          0.5873382244987757,
-          0.5019153341632077,
-          0.5856528708088332,
-          0.17026218155321735,
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+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.052115</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         Grear      Gfront  DCP (kW)         DNI         DHI  \\\n",
+       "2020-01-01 00:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
+       "2020-01-01 01:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
+       "2020-01-01 02:00:00   0.000000    0.000000  0.000000    0.000000    0.006899   \n",
+       "2020-01-01 03:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
+       "2020-01-01 04:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
+       "2020-01-01 05:00:00   0.000000    0.000000  0.000000    0.000000    0.007147   \n",
+       "2020-01-01 06:00:00   0.000000    0.000000  0.000000    0.224083    0.000000   \n",
+       "2020-01-01 07:00:00   0.952828   10.864534  0.011111   29.900648    9.146110   \n",
+       "2020-01-01 08:00:00   5.280836   62.891234  0.072767   39.650845   45.072811   \n",
+       "2020-01-01 09:00:00  25.020240  424.175198  0.487038  488.902252   92.055008   \n",
+       "2020-01-01 10:00:00  22.112267  140.597987  0.170311   40.219421  139.379303   \n",
+       "2020-01-01 11:00:00  15.243913  136.514177  0.159731    1.458432  146.268784   \n",
+       "2020-01-01 12:00:00  15.045047  138.871464  0.162195    7.297924  143.908936   \n",
+       "2020-01-01 13:00:00  32.694059  421.791129  0.485976  514.294067  142.040833   \n",
+       "2020-01-01 14:00:00  28.891263  547.687319  0.626409  695.355957   87.838135   \n",
+       "2020-01-01 15:00:00   5.155149  454.184026  0.503649  704.084229   39.767941   \n",
+       "2020-01-01 16:00:00   1.067853   23.427810  0.023300   64.097702   13.479426   \n",
+       "2020-01-01 17:00:00   0.000000    0.000000  0.000000    0.118982    0.056990   \n",
+       "2020-01-01 18:00:00   0.000000    0.000000  0.000000    0.074463    0.000000   \n",
+       "2020-01-01 19:00:00   0.000000    0.000000  0.000000    0.040330    0.011045   \n",
+       "2020-01-01 20:00:00   0.000000    0.000000  0.000000    0.000000    0.001485   \n",
+       "2020-01-01 21:00:00   0.000000    0.000000  0.000000    0.063725    0.000000   \n",
+       "2020-01-01 22:00:00   0.000000    0.000000  0.000000    0.000000    0.000000   \n",
+       "2020-01-01 23:00:00   0.000000    0.000000  0.000000    0.052115    0.000000   \n",
+       "\n",
+       "                     alb  \n",
+       "2020-01-01 00:00:00  0.2  \n",
+       "2020-01-01 01:00:00  0.2  \n",
+       "2020-01-01 02:00:00  0.2  \n",
+       "2020-01-01 03:00:00  0.2  \n",
+       "2020-01-01 04:00:00  0.2  \n",
+       "2020-01-01 05:00:00  0.2  \n",
+       "2020-01-01 06:00:00  0.2  \n",
+       "2020-01-01 07:00:00  0.2  \n",
+       "2020-01-01 08:00:00  0.2  \n",
+       "2020-01-01 09:00:00  0.2  \n",
+       "2020-01-01 10:00:00  0.2  \n",
+       "2020-01-01 11:00:00  0.2  \n",
+       "2020-01-01 12:00:00  0.2  \n",
+       "2020-01-01 13:00:00  0.2  \n",
+       "2020-01-01 14:00:00  0.2  \n",
+       "2020-01-01 15:00:00  0.2  \n",
+       "2020-01-01 16:00:00  0.2  \n",
+       "2020-01-01 17:00:00  0.2  \n",
+       "2020-01-01 18:00:00  0.2  \n",
+       "2020-01-01 19:00:00  0.2  \n",
+       "2020-01-01 20:00:00  0.2  \n",
+       "2020-01-01 21:00:00  0.2  \n",
+       "2020-01-01 22:00:00  0.2  \n",
+       "2020-01-01 23:00:00  0.2  "
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weatherfile = pd.read_csv(solar_resource_file, skiprows=2)\n",
+    "timestamps = pd.to_datetime(weatherfile[['Year','Month','Day','Hour']])\n",
+    "df.index = timestamps\n",
+    "#df=df.rename_axis(\"index\")\n",
+    "df.head(24)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "deb3ee05",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly.express as px\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "4c0cdea0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "startdate = '2020-11-06 0:0:0'\n",
+    "enddate = '2020-11-06 23:0:0'\n",
+    "\n",
+    "mybirthday = df[(df.index>startdate) & (df.index<enddate)]\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "plt.plot(mybirthday.DNI, label='DNI')\n",
+    "plt.plot(mybirthday.Gfront, label='Front')\n",
+    "plt.plot(mybirthday.Grear, label='Rear')\n",
+    "plt.ylabel(\"Irradiance [W/m$^2$]\")\n",
+    "plt.legend()\n",
+    "fig.autofmt_xdate()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "eb96c79f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "startdate = '2020-11-08 0:0:0'\n",
+    "enddate = '2020-11-08 23:0:0'\n",
+    "\n",
+    "mybirthday = df[(df.index>startdate) & (df.index<enddate)]\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "plt.plot(mybirthday.DNI, label='DNI')\n",
+    "plt.plot(mybirthday.Gfront, label='Front')\n",
+    "plt.plot(mybirthday.Grear, label='Rear')\n",
+    "plt.ylabel(\"Irradiance [W/m$^2$]\")\n",
+    "plt.legend()\n",
+    "fig.autofmt_xdate()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "c9ae8080",
+   "metadata": {},
+   "source": [
+    "We can also explore with plotly any of the columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "4a203939",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "variable=DCP (kW)<br>index=%{x}<br>value=%{y}<extra></extra>",
+         "legendgroup": "DCP (kW)",
+         "line": {
+          "color": "#636efa",
+          "dash": "solid"
+         },
+         "marker": {
+          "symbol": "circle"
+         },
+         "mode": "lines",
+         "name": "DCP (kW)",
+         "showlegend": true,
+         "type": "scattergl",
+         "x": [
+          "2020-01-01T00:00:00.000000000",
+          "2020-01-01T01:00:00.000000000",
+          "2020-01-01T02:00:00.000000000",
+          "2020-01-01T03:00:00.000000000",
+          "2020-01-01T04:00:00.000000000",
+          "2020-01-01T05:00:00.000000000",
+          "2020-01-01T06:00:00.000000000",
+          "2020-01-01T07:00:00.000000000",
+          "2020-01-01T08:00:00.000000000",
+          "2020-01-01T09:00:00.000000000",
+          "2020-01-01T10:00:00.000000000",
+          "2020-01-01T11:00:00.000000000",
+          "2020-01-01T12:00:00.000000000",
+          "2020-01-01T13:00:00.000000000",
+          "2020-01-01T14:00:00.000000000",
+          "2020-01-01T15:00:00.000000000",
+          "2020-01-01T16:00:00.000000000",
+          "2020-01-01T17:00:00.000000000",
+          "2020-01-01T18:00:00.000000000",
+          "2020-01-01T19:00:00.000000000",
+          "2020-01-01T20:00:00.000000000",
+          "2020-01-01T21:00:00.000000000",
+          "2020-01-01T22:00:00.000000000",
+          "2020-01-01T23:00:00.000000000",
+          "2020-01-02T00:00:00.000000000",
+          "2020-01-02T01:00:00.000000000",
+          "2020-01-02T02:00:00.000000000",
+          "2020-01-02T03:00:00.000000000",
+          "2020-01-02T04:00:00.000000000",
+          "2020-01-02T05:00:00.000000000",
+          "2020-01-02T06:00:00.000000000",
+          "2020-01-02T07:00:00.000000000",
+          "2020-01-02T08:00:00.000000000",
+          "2020-01-02T09:00:00.000000000",
+          "2020-01-02T10:00:00.000000000",
+          "2020-01-02T11:00:00.000000000",
+          "2020-01-02T12:00:00.000000000",
+          "2020-01-02T13:00:00.000000000",
+          "2020-01-02T14:00:00.000000000",
+          "2020-01-02T15:00:00.000000000",
+          "2020-01-02T16:00:00.000000000",
+          "2020-01-02T17:00:00.000000000",
+          "2020-01-02T18:00:00.000000000",
+          "2020-01-02T19:00:00.000000000",
+          "2020-01-02T20:00:00.000000000",
+          "2020-01-02T21:00:00.000000000",
+          "2020-01-02T22:00:00.000000000",
+          "2020-01-02T23:00:00.000000000",
+          "2020-01-03T00:00:00.000000000",
+          "2020-01-03T01:00:00.000000000",
+          "2020-01-03T02:00:00.000000000",
+          "2020-01-03T03:00:00.000000000",
+          "2020-01-03T04:00:00.000000000",
+          "2020-01-03T05:00:00.000000000",
+          "2020-01-03T06:00:00.000000000",
+          "2020-01-03T07:00:00.000000000",
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+          "dtype": "f8"
+         },
          "yaxis": "y"
         }
        ],
@@ -27924,57 +19171,6 @@
             "type": "heatmap"
            }
           ],
-          "heatmapgl": [
-           {
-            "colorbar": {
-             "outlinewidth": 0,
-             "ticks": ""
-            },
-            "colorscale": [
-             [
-              0,
-              "#0d0887"
-             ],
-             [
-              0.1111111111111111,
-              "#46039f"
-             ],
-             [
-              0.2222222222222222,
-              "#7201a8"
-             ],
-             [
-              0.3333333333333333,
-              "#9c179e"
-             ],
-             [
-              0.4444444444444444,
-              "#bd3786"
-             ],
-             [
-              0.5555555555555556,
-              "#d8576b"
-             ],
-             [
-              0.6666666666666666,
-              "#ed7953"
-             ],
-             [
-              0.7777777777777778,
-              "#fb9f3a"
-             ],
-             [
-              0.8888888888888888,
-              "#fdca26"
-             ],
-             [
-              1,
-              "#f0f921"
-             ]
-            ],
-            "type": "heatmapgl"
-           }
-          ],
           "histogram": [
            {
             "marker": {
@@ -28175,6 +19371,17 @@
             "type": "scattergl"
            }
           ],
+          "scattermap": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattermap"
+           }
+          ],
           "scattermapbox": [
            {
             "marker": {
@@ -28623,7 +19830,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 39,
    "id": "bb28fb2e",
    "metadata": {},
    "outputs": [],
@@ -28646,7 +19853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 40,
    "id": "e278e073",
    "metadata": {},
    "outputs": [],
@@ -28669,7 +19876,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 41,
    "id": "00d1211e",
    "metadata": {},
    "outputs": [],
@@ -28696,7 +19903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 42,
    "id": "1b525260",
    "metadata": {},
    "outputs": [],
@@ -28718,7 +19925,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 43,
    "id": "36fcd28d",
    "metadata": {},
    "outputs": [],
@@ -28741,7 +19948,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 44,
    "id": "5303d438",
    "metadata": {},
    "outputs": [],
@@ -28754,7 +19961,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pysam_build_3.10",
+   "display_name": "pysam_build_3.12",
    "language": "python",
    "name": "python3"
   },
@@ -28768,7 +19975,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/Examples/SelectingModuleandInverterExample/pySAM_Pvsamv1_default_values.xlsx b/Examples/SelectingModuleandInverterExample/pySAM_Pvsamv1_default_values.xlsx
index 6356150..90b52bb 100644
Binary files a/Examples/SelectingModuleandInverterExample/pySAM_Pvsamv1_default_values.xlsx and b/Examples/SelectingModuleandInverterExample/pySAM_Pvsamv1_default_values.xlsx differ
diff --git a/Examples/UtilityRateForecastExample.py b/Examples/UtilityRateForecastExample.py
index 85a67b6..ec37b63 100644
--- a/Examples/UtilityRateForecastExample.py
+++ b/Examples/UtilityRateForecastExample.py
@@ -15,7 +15,7 @@
 This can either be run with all of the steps at once (single call to execute()) to generate an array of prices
 or by calling execute repeateadly, potentially in the loop with a model-predictive controller for energy storage
 
-Most recently tested against PySAM 7.0.0
+Most recently tested against PySAM 7.1.0
 """
 
 # Get a key from https://api.openei.org:443
diff --git a/Examples/UtilityRatesExample.py b/Examples/UtilityRatesExample.py
index c381e3e..61a04f4 100644
--- a/Examples/UtilityRatesExample.py
+++ b/Examples/UtilityRatesExample.py
@@ -6,7 +6,7 @@
 Additional financial models, inputs, and outputs can be found at:
 * PV: https://nrel-pysam.readthedocs.io/en/master/modules/Utilityrate5.html
 
-Most recently tested against PySAM 76.0.0
+Most recently tested against PySAM 7.1.0
 Requires: nrel-pysam, requests
 
 @author: brtietz
diff --git a/Examples/Windpower_Example/windpower-example.py b/Examples/Windpower_Example/windpower-example.py
index 9a63eef..6bb9e15 100644
--- a/Examples/Windpower_Example/windpower-example.py
+++ b/Examples/Windpower_Example/windpower-example.py
@@ -6,7 +6,7 @@
 Created with PySAM 4.2.0 in Python 3.8.7. Last tested with PySAM 4.2.0 with
 code generated by SAM 2022.11.21 r1 SSC 279.
 
-Most recently tested with PySAM 6.0.0
+Most recently tested with PySAM 7.1.0
 
 '''
 
diff --git a/Examples/Windpower_Example/windpower-inputs.json b/Examples/Windpower_Example/windpower-inputs.json
index eb9eca6..2cb7930 100644
--- a/Examples/Windpower_Example/windpower-inputs.json
+++ b/Examples/Windpower_Example/windpower-inputs.json
@@ -36,6 +36,6 @@
 	"turb_hysteresis_loss" : 0.40000000000000002,
 	"turb_perf_loss" : 1.1000000000000001,
 	"turb_specific_loss" : 0.81000000000000005,
-	"constant" : 0,
+	"adjust_constant" : 0,
 	"total_uncert" : 12.085000000000001
 }
diff --git a/RELEASE.md b/RELEASE.md
index aa9d70b..0a5f83e 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -1,5 +1,8 @@
 # Release Notes
 
+## Version 7.1.0, July 24, 2025 - SAM 2025.4.16 Revision 1, SSC Version 303
+* [SAM Release updates for Version 2025.4.16 Revision 1](https://nrel.github.io/SAM/doc/releasenotes.html)
+
 ## Version 7.0.0, Apr, 17 2025 - SAM 2025.4.16, SSC Version 302
 * [SAM Release updates for Version 2025.4.16](https://nrel.github.io/SAM/doc/releasenotes.html)
 * Added GETEM model and equations for Geothermal (#189)
diff --git a/build_conda.sh b/build_conda.sh
index e775aa7..1430178 100755
--- a/build_conda.sh
+++ b/build_conda.sh
@@ -15,7 +15,7 @@ yes | conda install conda-build
 yes | conda activate base
 conda update -n base -c defaults conda
 
-for PYTHONVER in 3.8 3.9 3.10 3.11 3.12
+for PYTHONVER in 3.9 3.10 3.11 3.12 3.13
 do
    export PYTHONVER
    conda-build conda --output-folder=$DIST_DIR --python=$PYTHONVER --prefix-length=0 || exit
diff --git a/build_unix.sh b/build_unix.sh
index 8cc1a04..e807f28 100755
--- a/build_unix.sh
+++ b/build_unix.sh
@@ -58,7 +58,7 @@ fi
 
 rename -s linux manylinux2014 $PYSAMDIR/dist/*-linux_*
 docker pull continuumio/anaconda3
-docker run --rm --env PYSAMDIR=/io/pysam -v $(pwd):/io continuumio/anaconda /io/pysam/build_conda.sh
+docker run --rm --env PYSAMDIR=/io/pysam -v $(pwd):/io continuumio/anaconda3 /io/pysam/build_conda.sh
 
 # anaconda upload -u nrel $PYSAMDIR/dist/osx-64/*.tar.bz2
 # anaconda upload -u nrel $PYSAMDIR/dist/linux-64/*.tar.bz2
diff --git a/conda/build.sh b/conda/build.sh
index 8a655fe..f923dc9 100644
--- a/conda/build.sh
+++ b/conda/build.sh
@@ -17,7 +17,8 @@ if [[ $OS_NAME == 'other' ]]; then
   exit 1
 fi
 
-pattern=$DIST_DIR/NREL_PySAM-*$VERSION*"${PYTHONVER//.}"*$OS_NAME*whl
+# pattern=$DIST_DIR/NREL_PySAM-*$VERSION*"${PYTHONVER//.}"*$OS_NAME*whl
+pattern=$DIST_DIR/nrel_pysam-*$VERSION*"${PYTHONVER//.}"*$OS_NAME*whl
 FILE=( $pattern )
 
 if [ -f "$FILE" ]; then
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 346c404..f0833ec 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,3 +1,3 @@
-NREL-PySAM==7.0.0
+NREL-PySAM==7.1.0
 pandas
 sphinx_rtd_theme
diff --git a/docs/version_changes/7.1.0.rst b/docs/version_changes/7.1.0.rst
new file mode 100644
index 0000000..6445888
--- /dev/null
+++ b/docs/version_changes/7.1.0.rst
@@ -0,0 +1,19 @@
+.. 7.1.0:
+
+Version 7.1.0
+===============================================
+
+Version 7.1.0, released July 24, 2025, corresponds to SAM 2025.4.16 Revision 1, SSC 303.
+
+This page compares the PySAM Modules' input variables and the defaults for these input variables 
+between the current release and the last release.
+
+This helps track which variables and defaults have changed between releases to make it easier to notify users during version upgrade.
+
+Below are lists for each PySAM Module:
+    1. New Default configurations
+    2. Removed Default configurations
+    3. Modified Variables: New variables, Removed variables and Type-changed variables
+    4. Modified Default Values
+
+No changes
diff --git a/docs/versions.rst b/docs/versions.rst
index 51b5874..5d8c82f 100644
--- a/docs/versions.rst
+++ b/docs/versions.rst
@@ -8,6 +8,7 @@ The list below tracks changes in variables between consecutive PySAM versions.
 .. toctree::
     :maxdepth: 1
 
+    version_changes/7.1.0.rst
     version_changes/7.0.0.rst
     version_changes/6.0.0.rst
     version_changes/5.1.0.rst
diff --git a/files/version.py b/files/version.py
index 5220ac1..dc8ddee 100644
--- a/files/version.py
+++ b/files/version.py
@@ -1 +1 @@
-__version__ = '7.0.0'
+__version__ = '7.1.0'
diff --git a/modules/FresnelPhysical.c b/modules/FresnelPhysical.c
index a0be45a..1abcd8d 100644
--- a/modules/FresnelPhysical.c
+++ b/modules/FresnelPhysical.c
@@ -6500,6 +6500,12 @@ Outputs_get_rec_thermal_eff(VarGroupObject *self, void *closure)
 	return PySAM_array_getter(SAM_FresnelPhysical_Outputs_rec_thermal_eff_aget, self->data_ptr);
 }
 
+static PyObject *
+Outputs_get_rec_time_in_startup(VarGroupObject *self, void *closure)
+{
+	return PySAM_array_getter(SAM_FresnelPhysical_Outputs_rec_time_in_startup_aget, self->data_ptr);
+}
+
 static PyObject *
 Outputs_get_recirculating(VarGroupObject *self, void *closure)
 {
@@ -7266,6 +7272,9 @@ static PyGetSetDef Outputs_getset[] = {
 {"rec_thermal_eff", (getter)Outputs_get_rec_thermal_eff,(setter)0,
 	PyDoc_STR("*sequence*: Receiver thermal efficiency"),
  	NULL},
+{"rec_time_in_startup", (getter)Outputs_get_rec_time_in_startup,(setter)0,
+	PyDoc_STR("*sequence*: Field time at startup [min]"),
+ 	NULL},
 {"recirculating", (getter)Outputs_get_recirculating,(setter)0,
 	PyDoc_STR("*sequence*: Field recirculating (bypass valve open) [-]"),
  	NULL},
diff --git a/modules/FresnelPhysicalIph.c b/modules/FresnelPhysicalIph.c
index 9210794..c1786b1 100644
--- a/modules/FresnelPhysicalIph.c
+++ b/modules/FresnelPhysicalIph.c
@@ -6599,6 +6599,12 @@ Outputs_get_rec_thermal_eff(VarGroupObject *self, void *closure)
 	return PySAM_array_getter(SAM_FresnelPhysicalIph_Outputs_rec_thermal_eff_aget, self->data_ptr);
 }
 
+static PyObject *
+Outputs_get_rec_time_in_startup(VarGroupObject *self, void *closure)
+{
+	return PySAM_array_getter(SAM_FresnelPhysicalIph_Outputs_rec_time_in_startup_aget, self->data_ptr);
+}
+
 static PyObject *
 Outputs_get_recirculating(VarGroupObject *self, void *closure)
 {
@@ -7401,6 +7407,9 @@ static PyGetSetDef Outputs_getset[] = {
 {"rec_thermal_eff", (getter)Outputs_get_rec_thermal_eff,(setter)0,
 	PyDoc_STR("*sequence*: Receiver thermal efficiency"),
  	NULL},
+{"rec_time_in_startup", (getter)Outputs_get_rec_time_in_startup,(setter)0,
+	PyDoc_STR("*sequence*: Field time at startup [min]"),
+ 	NULL},
 {"recirculating", (getter)Outputs_get_recirculating,(setter)0,
 	PyDoc_STR("*sequence*: Field recirculating (bypass valve open) [-]"),
  	NULL},
diff --git a/modules/TroughPhysical.c b/modules/TroughPhysical.c
index e4a3b37..ba4316a 100644
--- a/modules/TroughPhysical.c
+++ b/modules/TroughPhysical.c
@@ -8058,6 +8058,12 @@ Outputs_get_rec_op_mode_final(VarGroupObject *self, void *closure)
 	return PySAM_array_getter(SAM_TroughPhysical_Outputs_rec_op_mode_final_aget, self->data_ptr);
 }
 
+static PyObject *
+Outputs_get_rec_time_in_startup(VarGroupObject *self, void *closure)
+{
+	return PySAM_array_getter(SAM_TroughPhysical_Outputs_rec_time_in_startup_aget, self->data_ptr);
+}
+
 static PyObject *
 Outputs_get_recirculating(VarGroupObject *self, void *closure)
 {
@@ -9067,6 +9073,9 @@ static PyGetSetDef Outputs_getset[] = {
 {"rec_op_mode_final", (getter)Outputs_get_rec_op_mode_final,(setter)0,
 	PyDoc_STR("*sequence*: Final receiver operating mode 0: off, 1: startup, 2: on [-]"),
  	NULL},
+{"rec_time_in_startup", (getter)Outputs_get_rec_time_in_startup,(setter)0,
+	PyDoc_STR("*sequence*: Field time at startup [min]"),
+ 	NULL},
 {"recirculating", (getter)Outputs_get_recirculating,(setter)0,
 	PyDoc_STR("*sequence*: Field recirculating (bypass valve open) [-]"),
  	NULL},
diff --git a/modules/TroughPhysicalIph.c b/modules/TroughPhysicalIph.c
index ea96530..790d2ec 100644
--- a/modules/TroughPhysicalIph.c
+++ b/modules/TroughPhysicalIph.c
@@ -8395,6 +8395,12 @@ Outputs_get_qinc_costh(VarGroupObject *self, void *closure)
 	return PySAM_array_getter(SAM_TroughPhysicalIph_Outputs_qinc_costh_aget, self->data_ptr);
 }
 
+static PyObject *
+Outputs_get_rec_time_in_startup(VarGroupObject *self, void *closure)
+{
+	return PySAM_array_getter(SAM_TroughPhysicalIph_Outputs_rec_time_in_startup_aget, self->data_ptr);
+}
+
 static PyObject *
 Outputs_get_recirculating(VarGroupObject *self, void *closure)
 {
@@ -9452,6 +9458,9 @@ static PyGetSetDef Outputs_getset[] = {
 {"qinc_costh", (getter)Outputs_get_qinc_costh,(setter)0,
 	PyDoc_STR("*sequence*: Field thermal power incident after cosine [MWt]"),
  	NULL},
+{"rec_time_in_startup", (getter)Outputs_get_rec_time_in_startup,(setter)0,
+	PyDoc_STR("*sequence*: Field time at startup [min]"),
+ 	NULL},
 {"recirculating", (getter)Outputs_get_recirculating,(setter)0,
 	PyDoc_STR("*sequence*: Field recirculating (bypass valve open) [-]"),
  	NULL},
diff --git a/stubs/stubs/FresnelPhysical.pyi b/stubs/stubs/FresnelPhysical.pyi
index 40a4fc4..e1dea75 100644
--- a/stubs/stubs/FresnelPhysical.pyi
+++ b/stubs/stubs/FresnelPhysical.pyi
@@ -722,6 +722,7 @@ class FresnelPhysical(object):
 		q_pc_startup = tuple
 		q_tes_heater = tuple
 		rec_thermal_eff = tuple
+		rec_time_in_startup = tuple
 		recirculating = tuple
 		rh = tuple
 		sales_tax_total = float
diff --git a/stubs/stubs/FresnelPhysicalIph.pyi b/stubs/stubs/FresnelPhysicalIph.pyi
index fe056f9..5bb29ed 100644
--- a/stubs/stubs/FresnelPhysicalIph.pyi
+++ b/stubs/stubs/FresnelPhysicalIph.pyi
@@ -731,6 +731,7 @@ class FresnelPhysicalIph(object):
 		q_inc_sf_tot = tuple
 		q_tes_heater = tuple
 		rec_thermal_eff = tuple
+		rec_time_in_startup = tuple
 		recirculating = tuple
 		rh = tuple
 		sales_tax_total = float
diff --git a/stubs/stubs/TroughPhysical.pyi b/stubs/stubs/TroughPhysical.pyi
index 307ccf9..679b183 100644
--- a/stubs/stubs/TroughPhysical.pyi
+++ b/stubs/stubs/TroughPhysical.pyi
@@ -851,6 +851,7 @@ class TroughPhysical(object):
 		q_tes_heater = tuple
 		qinc_costh = tuple
 		rec_op_mode_final = tuple
+		rec_time_in_startup = tuple
 		recirculating = tuple
 		required_number_of_loops_for_SM1 = float
 		rh = tuple
diff --git a/stubs/stubs/TroughPhysicalIph.pyi b/stubs/stubs/TroughPhysicalIph.pyi
index 177af6a..93c2ed6 100644
--- a/stubs/stubs/TroughPhysicalIph.pyi
+++ b/stubs/stubs/TroughPhysicalIph.pyi
@@ -914,6 +914,7 @@ class TroughPhysicalIph(object):
 		q_tes = float
 		q_tes_heater = tuple
 		qinc_costh = tuple
+		rec_time_in_startup = tuple
 		recirculating = tuple
 		required_number_of_loops_for_SM1 = float
 		rh = tuple