# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:28:43 2015 @author: """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.968, 148.032)}, 'Y': {'range': (-36.032, -35.968)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } arrays = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data') ndvi = a.applyBandMath(arrays, '((array1 - array2) / (array1 + array2))', 'ndvi') arrays2 = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data2') ndvi2 = a.applyBandMath(arrays2, '((array1 - 2.0*array2) / (array2))', 'ndvi2') average = a.applyBandMath([ndvi, ndvi2], '((array1 + array2) / 2)', 'average') pq_data = a.createArray('LS5TMPQ', ['PQ'], dimensions, 'pq_data') mask = a.applyCloudMask(average, pq_data, 'mask') median_t = a.applyGenericReduction(mask, ['T'], 'median(array1)', 'medianT') result = e.executePlan(a.plan) plot(e.cache['medianT'])
# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:25:35 2015 @author: """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.968, 148.032)}, 'Y': {'range': (-36.032, -35.968)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } arrays = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data') ndvi = a.applyBandMath(arrays, '((array1 - array2) / (array1 + array2))', 'ndvi') arrays2 = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data2') ndvi2 = a.applyBandMath(arrays2, '((array1 - array2) / (array1 + array2))', 'ndvi2') average = a.applyBandMath([ndvi, ndvi2], '((array1 + array2) / 2)', 'average') result = e.executePlan(a.plan) plot(e.cache['average'])
# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:03:49 2015 @author: """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.968, 148.032)}, 'Y': {'range': (-36.032, -35.968)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } ndvi = a.applySensorSpecificBandMath('LS5TM', 'ndvi', dimensions, 'step1_get_data', 'step2_ndvi') result = e.executePlan(a.plan) plot(e.cache['ndvi'])
# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:03:49 2015 @author: """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.0, 148.0)}, 'Y': {'range': (-37.0, -36.0)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } arrays = a.createArray('LS5TM', ['B40',], dimensions, 'get_data') #ndvi = a.applyBandMath(arrays, '((array1 - array2) / (array1 + array2))', 'ndvi') e.executePlan(a.plan) plot(e.cache['get_data'])
# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:27:20 2015 @author: """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.968, 148.032)}, 'Y': {'range': (-36.032, -35.968)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } arrays = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data') ndvi = a.applyBandMath(arrays, '((array1 - array2) / (array1 + array2))', 'ndvi') arrays2 = a.createArray('LS5TM', ['B40', 'B30'], dimensions, 'get_data2') ndvi2 = a.applyBandMath(arrays2, '((array1 - array2) / (array1 + array2))', 'ndvi2') average = a.applyBandMath([ndvi, ndvi2], '((array1 + array2) / 2)', 'average') pq_data = a.createArray('LS5TMPQ', ['PQ'], dimensions, 'pq_data') mask = a.applyCloudMask(average, pq_data, 'mask') result = e.executePlan(a.plan) plot(e.cache['mask'])
# -*- coding: utf-8 -*- """ Created on Tue Jul 14 15:09:43 2015 @author: woo409 """ from pprint import pprint from datetime import datetime from analytics import Analytics from execution_engine import ExecutionEngine from analytics_utils import plot a = Analytics() e = ExecutionEngine() dimensions = {'X': {'range': (147.968, 148.032)}, 'Y': {'range': (-36.032, -35.968)}, 'T': {'range': (1262304000.0, 1325375999.999999)}, } arrays = a.createArray('LS5TM', ['B40'], dimensions, 'get_data') median_xt = a.applyGenericReduction(arrays, ['X', 'Y'], 'median(array1)', 'medianXY') result = e.executePlan(a.plan) plot(e.cache['medianXY'])