from airflow.utils.trigger_rule import TriggerRule from datetime import timedelta from pprint import pprint _params = {{params}} _steps = { 'consulta': { 'algorithm': "just-query", 'version': '1.0', 'queue': queue_utils.assign_queue(input_type='multi_temporal_area', time_range=_params['time_ranges'][0], lat=_params['lat'], lon=_params['lon']), 'params': {}, }, 'pca': { 'algorithm': "deteccion-cambios-pca-wf", 'version': '1.0', 'queue': queue_utils.assign_queue(input_type='multi_area', lat=_params['lat'], lon=_params['lon']), 'params': {}, 'del_prev_result': _params['elimina_resultados_anteriores'],
from datetime import timedelta from pprint import pprint _params = { 'lat': (9, 11), 'lon': (-76, -74), 'time_ranges': ("2013-01-01", "2015-12-31"), 'products': ["LS8_OLI_LASRC"], 'mosaic': True, 'generate-geotiff': True } _queues = { 'wofs-wf': queue_utils.assign_queue(), 'joiner-reduce-wofs': queue_utils.assign_queue(input_type='multi_temporal_unidad', time_range=_params['time_ranges'], unidades=len(_params['products'])), 'wofs-time-series-wf': queue_utils.assign_queue(input_type='multi_temporal_unidad', time_range=_params['time_ranges'], unidades=len(_params['products'])), 'joiner': queue_utils.assign_queue(input_type='multi_temporal_unidad_area', time_range=_params['time_ranges'], lat=_params['lat'], lon=_params['lon'], unidades=len(_params['products'])), }
from airflow.models import DAG from airflow.operators import CDColQueryOperator, CDColFromFileOperator, CDColReduceOperator from airflow.operators.python_operator import PythonOperator from cdcol_utils import dag_utils, queue_utils, other_utils from airflow.utils.trigger_rule import TriggerRule from datetime import timedelta from pprint import pprint _params = {{params}} _steps = { 'ndvi': { 'algorithm': "ndvi-wf", 'version': '1.0', 'queue': queue_utils.assign_queue(), 'params': {}, 'del_prev_result': _params['elimina_resultados_anteriores'], }, 'bosque': { 'algorithm': "bosque-no-bosque-wf", 'version': '1.0', 'queue': queue_utils.assign_queue(), 'params': { 'ndvi_threshold': _params['ndvi_threshold'], 'vegetation_rate': _params['vegetation_rate'], 'slice_size': _params['slice_size'] }, 'del_prev_result': _params['elimina_resultados_anteriores'], }, 'mosaico': {
from pprint import pprint _params = { 'lat': (4,6), 'lon': (-74,-72), 'time_ranges': [("2016-01-01", "2016-12-31"),("2017-01-01", "2017-12-31")], 'bands': ["blue", "green", "red", "nir", "swir1", "swir2"], 'minValid':1, 'normalized':True, 'products': ["LS8_OLI_LASRC"], 'mosaic': False } _queues = { 'mascara-landsat': queue_utils.assign_queue(input_type='multi_temporal', time_range=_params['time_ranges'][0]), 'joiner-reduce': queue_utils.assign_queue(input_type='multi_temporal_unidad', time_range=_params['time_ranges'][0], unidades=len(_params['products'])), 'compuesto-temporal-medianas-wf':queue_utils.assign_queue(input_type='multi_temporal_unidad', time_range=_params['time_ranges'][0], unidades=len(_params['products']) ), 'ndvi-wf' : queue_utils.assign_queue(), 'joiner': queue_utils.assign_queue(input_type='multi_area',lat=_params['lat'], lon=_params['lon'] ), 'test-reduce': queue_utils.assign_queue(), } args = { 'owner': 'cubo', 'start_date': airflow.utils.dates.days_ago(2), 'execID': "ndvi_anomaly", 'product': "LS8_OLI_LASRC" } dag = DAG(
_params = { 'lat': (9, 11), 'lon': (-76, -75), 'time_ranges': [("2014-01-01", "2014-12-31"), ("2015-01-01", "2015-12-31")], 'bands': ["blue", "green", "red", "nir", "swir1", "swir2", "pixel_qa"], 'minValid': 1, 'normalized': True, 'products': ["LS7_ETM_LEDAPS"], 'elimina_resultados_anteriores': True } _steps = { 'mascara': { 'algorithm': "mascara-landsat", 'version': '1.0', 'queue': queue_utils.assign_queue(input_type='multi_temporal', time_range=_params['time_ranges'][0]), 'params': {'bands': _params['bands']}, }, 'medianas': { 'algorithm': "compuesto-temporal-medianas-wf", 'version': '1.0', 'queue': queue_utils.assign_queue( input_type='multi_temporal_unidad', time_range=_params['time_ranges'][0], unidades=len(_params['products'])), 'params': { 'normalized': _params['normalized'], 'bands': _params['bands'], 'minValid': _params['minValid'], }, 'del_prev_result': _params['elimina_resultados_anteriores'],
_params = { 'lat': (9, 11), 'lon': (-76, -75), 'time_ranges': [("2014-01-01", "2014-12-31"), ("2015-01-01", "2015-12-31")], 'bands': ["blue", "green", "red", "nir", "swir1", "swir2", "pixel_qa"], 'minValid': 1, 'normalized': True, 'products': ["LS7_ETM_LEDAPS"], } _steps = { 'mascara': { 'algorithm': "mascara-landsat", 'version': '1.0', 'queue': queue_utils.assign_queue( input_type='multi_temporal', time_range=_params['time_ranges'][0]), 'params': {'bands': _params['bands']}, } } args = { 'owner': 'mp.mancipe10', 'start_date': airflow.utils.dates.days_ago(2), 'execID': "mp.mancipe10_pca_paso_4_consulta_varios_tiles", 'product': _params['products'][0] } dag = DAG( dag_id=args["execID"], default_args=args,
from datetime import timedelta from pprint import pprint _params = { 'lat': (9, 11), 'lon': (-76, -75), 'time_ranges': ("2010-01-01", "2011-12-31"), 'products': ["LS7_ETM_LEDAPS"], } _steps = { 'wofs': { 'algorithm': "wofs-wf", 'version': '1.0', 'queue': queue_utils.assign_queue(), }, } args = { 'owner': 'mp.mancipe10', 'start_date': airflow.utils.dates.days_ago(2), 'execID': "mp.mancipe10_wofs_paso_3_clasificacion_varios_anhos", 'product': _params['products'][0] } dag = DAG(dag_id=args['execID'], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120))