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‎gee/time-series/time-series-test.ipynb

Lines changed: 47 additions & 47 deletions
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@@ -148,6 +148,52 @@
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" return json_result"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'table': [{'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_max', 'y': [-20.298712891539253, -49.84760867764999, -142.94793314166145, -109.18966259438457, -3.420149071400374, -58.15354447984464, 103.67251847355419, -38.21928456404021, 120.44181660916729, 24.20228103633235, 69.75337084635794, 236.86592895579543, 31.309200901736403, 136.49544774126616, 626.0471677512078, 153.92202844297663, 540.6781601376028, 570.3179114784771, 631.2566358577483, 489.1332327970704, 430.31326066037946]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_mean', 'y': [-419.83891694877707, -115.24624374625806, -338.08701543914106, -327.76351891293075, -235.3787097780539, -120.9360827329493, -16.873152793465803, -296.4657966613747, 21.315652258027427, -127.64212673868843, -64.96720254065022, 105.68896813631554, -202.0944013612229, 45.98613771587721, 378.1512024981405, 99.12355714249806, 367.459162277705, 350.4101365387817, 414.3876350537403, 295.47827431915925, 187.29244171326425]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_min', 'y': [-657.3768248837287, -313.48870346864805, -484.03198491355397, -495.77653016354407, -427.33466048457467, -224.96154013474916, -176.66275127781682, -558.5186070584523, -131.9141536688394, -209.7385560542234, -242.31541637402643, -60.20113373989443, -447.72166485390426, -77.32880676360764, 130.57985092859963, -3.360473973414628, 130.76579666146336, 97.02612068747203, 119.12605242828886, 217.61299334799787, 129.88615464321902]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_mode', 'y': [-657.3768248837287, -91.01534204706195, -484.03198491355397, -495.77653016354407, -427.33466048457467, -144.40752254993913, -40.11878206694519, -558.5186070584523, 120.44181660916729, -152.17623544335902, 69.75337084635794, 236.86592895579543, -447.72166485390426, 136.49544774126616, 626.0471677512078, 153.92202844297663, 540.6781601376028, 570.3179114784771, 631.2566358577483, 282.8135320012375, 129.88615464321902]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_stdDev', 'y': [269.83319214734183, 102.3256853424134, 128.62496079449323, 141.1689891939797, 159.85795318599511, 68.22923572896032, 105.60673726217127, 207.46925137778126, 93.20902904567141, 86.32559826369666, 133.4296524952842, 111.64287385477353, 202.19786939755934, 86.48115932581523, 195.27424583731386, 63.69835562966978, 170.30542659011684, 175.2252617301482, 224.2658216475342, 104.78012909825429, 118.08292799111747]}], 'type': 'TimeSeriesTable', 'name': 'timeseries'}\n"
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]
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}
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],
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"source": [
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"logger.debug(\"Loading parameters.\")\n",
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"geojsons = json.loads(params.get(\"geojsons\"))\n",
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"year_initial = int(params.get(\"year_initial\"))\n",
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"year_final = int(params.get(\"year_final\"))\n",
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"trajectory_method = params.get(\"trajectory_method\")\n",
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"ndvi_gee_dataset = params.get(\"ndvi_gee_dataset\")\n",
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"climate_gee_dataset = params.get(\"climate_gee_dataset\")\n",
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"\n",
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"# Check the ENV. Are we running this locally or in prod?\n",
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"\n",
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"if params.get(\"ENV\") == \"dev\":\n",
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" EXECUTION_ID = str(random.randint(1000000, 99999999))\n",
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"else:\n",
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" EXECUTION_ID = params.get(\"EXECUTION_ID\", None)\n",
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"logger.debug(f\"Execution ID is {EXECUTION_ID}\")\n",
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"\n",
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"logger.debug(\"Running main script.\")\n",
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"# TODO: Right now timeseries will only work on the first geojson - this is\n",
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"# somewhat ok since for the most part this uses points, but should fix in\n",
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"# the future\n",
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"json_result = zonal_stats(\n",
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" geojsons[0],\n",
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" year_initial,\n",
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" year_final,\n",
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" trajectory_method,\n",
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" ndvi_gee_dataset,\n",
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" climate_gee_dataset,\n",
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" logger,\n",
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")\n",
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"print(json_result)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 41,
@@ -214,52 +260,6 @@
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"\n",
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"print(res_clean)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'table': [{'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_max', 'y': [-20.298712891539253, -49.84760867764999, -142.94793314166145, -109.18966259438457, -3.420149071400374, -58.15354447984464, 103.67251847355419, -38.21928456404021, 120.44181660916729, 24.20228103633235, 69.75337084635794, 236.86592895579543, 31.309200901736403, 136.49544774126616, 626.0471677512078, 153.92202844297663, 540.6781601376028, 570.3179114784771, 631.2566358577483, 489.1332327970704, 430.31326066037946]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_mean', 'y': [-419.83891694877707, -115.24624374625806, -338.08701543914106, -327.76351891293075, -235.3787097780539, -120.9360827329493, -16.873152793465803, -296.4657966613747, 21.315652258027427, -127.64212673868843, -64.96720254065022, 105.68896813631554, -202.0944013612229, 45.98613771587721, 378.1512024981405, 99.12355714249806, 367.459162277705, 350.4101365387817, 414.3876350537403, 295.47827431915925, 187.29244171326425]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_min', 'y': [-657.3768248837287, -313.48870346864805, -484.03198491355397, -495.77653016354407, -427.33466048457467, -224.96154013474916, -176.66275127781682, -558.5186070584523, -131.9141536688394, -209.7385560542234, -242.31541637402643, -60.20113373989443, -447.72166485390426, -77.32880676360764, 130.57985092859963, -3.360473973414628, 130.76579666146336, 97.02612068747203, 119.12605242828886, 217.61299334799787, 129.88615464321902]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_mode', 'y': [-657.3768248837287, -91.01534204706195, -484.03198491355397, -495.77653016354407, -427.33466048457467, -144.40752254993913, -40.11878206694519, -558.5186070584523, 120.44181660916729, -152.17623544335902, 69.75337084635794, 236.86592895579543, -447.72166485390426, 136.49544774126616, 626.0471677512078, 153.92202844297663, 540.6781601376028, 570.3179114784771, 631.2566358577483, 282.8135320012375, 129.88615464321902]}, {'time': [2001.0, 2002.0, 2003.0, 2004.0, 2005.0, 2006.0, 2007.0, 2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0], 'name': 'ndvi_stdDev', 'y': [269.83319214734183, 102.3256853424134, 128.62496079449323, 141.1689891939797, 159.85795318599511, 68.22923572896032, 105.60673726217127, 207.46925137778126, 93.20902904567141, 86.32559826369666, 133.4296524952842, 111.64287385477353, 202.19786939755934, 86.48115932581523, 195.27424583731386, 63.69835562966978, 170.30542659011684, 175.2252617301482, 224.2658216475342, 104.78012909825429, 118.08292799111747]}], 'type': 'TimeSeriesTable', 'name': 'timeseries'}\n"
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]
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}
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],
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"source": [
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"logger.debug(\"Loading parameters.\")\n",
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"geojsons = json.loads(params.get(\"geojsons\"))\n",
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"year_initial = int(params.get(\"year_initial\"))\n",
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"year_final = int(params.get(\"year_final\"))\n",
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"trajectory_method = params.get(\"trajectory_method\")\n",
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"ndvi_gee_dataset = params.get(\"ndvi_gee_dataset\")\n",
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"climate_gee_dataset = params.get(\"climate_gee_dataset\")\n",
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"\n",
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"# Check the ENV. Are we running this locally or in prod?\n",
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"\n",
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"if params.get(\"ENV\") == \"dev\":\n",
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" EXECUTION_ID = str(random.randint(1000000, 99999999))\n",
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"else:\n",
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" EXECUTION_ID = params.get(\"EXECUTION_ID\", None)\n",
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"logger.debug(f\"Execution ID is {EXECUTION_ID}\")\n",
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"\n",
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"logger.debug(\"Running main script.\")\n",
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"# TODO: Right now timeseries will only work on the first geojson - this is\n",
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"# somewhat ok since for the most part this uses points, but should fix in\n",
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"# the future\n",
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"json_result = zonal_stats(\n",
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" geojsons[0],\n",
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" year_initial,\n",
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" year_final,\n",
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" trajectory_method,\n",
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" ndvi_gee_dataset,\n",
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" climate_gee_dataset,\n",
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" logger,\n",
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")\n",
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"print(json_result)"
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]
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}
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],
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"metadata": {
@@ -278,7 +278,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.4"
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"version": "3.10.13"
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}
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},
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"nbformat": 4,

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