'start_date': airflow.utils.dates.days_ago(2), 'execID': "compuesto_de_medianas_normalizado_mosaico", 'product': "LS8_OLI_LASRC" } dag = DAG(dag_id=args['execID'], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) mascara_ls8 = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][0], params=_steps['mascara']['params'], queue=_steps['mascara']['queue'], dag=dag, task_id="consulta_cubo_" + _params['products'][0]) mascara_ls7_mosaic = CDColQueryOperator( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm=_steps['consulta']['algorithm'], version=_steps['consulta']['version'], product=_params['products'][1], params=_steps['consulta']['params'], queue=_steps['consulta']['queue'],
dag = DAG( dag_id=args['execID'], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) mascara_0 = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][2], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][2], params=_steps['mascara']['params'], queue=_steps['mascara']['queue'], dag=dag, task_id="mascara_" + _params['products'][2]['name'] ) if len(_params['products']) > 3: mascara_1 = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][2], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][3], params=_steps['mascara']['params'],
'execID': _params['execID'], 'product': "LS8_OLI_LASRC" } dag = DAG(dag_id=args['execID'], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) generic_step = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm=_steps['generic-step']['algorithm'], version=_steps['generic-step']['version'], product=_params['products'][0], params=_steps['generic-step']['params'], queue=_steps['generic-step']['queue'], dag=dag, task_id="generic-step_" + _params['products'][0]['name'], to_tiff=False, alg_folder=common.COMPLETE_ALGORITHMS_FOLDER) workflow = generic_step if _params['genera_mosaico'] and queue_utils.get_tiles(_params['lat'], _params['lon']) > 1: mosaico = dag_utils.OneReduce( workflow, task_id="mosaic", algorithm=_steps['mosaico']['algorithm'], version=_steps['mosaico']['version'],
'start_date': airflow.utils.dates.days_ago(2), 'execID': _params['execID'], 'product': "LS8_OLI_LASRC" } dag = DAG(dag_id=args["execID"], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) mascara_0 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][0], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][0], params=_steps['mascara']['params'], queue=_steps['mascara']['queue'], dag=dag, task_id="mascara_" + _params['products'][0]['name']) if len(_params['products']) > 1: mascara_1 = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][0], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][1], params=_steps['mascara']['params'],
'execID': "ndvi", 'product': "LS8_OLI_LASRC" } dag = DAG(dag_id=args["execID"], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) masked0 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={ 'normalized': _params['normalized'], 'bands': _params['bands'], 'minValid': _params['minValid'] }, queue=_queues['mascara-landsat'], dag=dag, task_id="masked_" + _params['products'][0]) if len(_params['products']) > 1: masked1 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product=_params['products'][1], params={
'start_date': airflow.utils.dates.days_ago(2), 'execID': "mp.mancipe10-paso-8-multiunidad-k-means-utils", 'product': _params['products'][0] } dag = DAG(dag_id='mp.mancipe10-paso-8-multiunidad-k-means-utils', default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) consulta_ls8 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={'bands': _params['bands']}, queue='airflow_small', dag=dag, taxprefix="masked_{}_".format( _params['products'][0])) consulta_ls7 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product=_params['products'][1], params={'bands': _params['bands']}, queue='airflow_small', dag=dag,
'start_date': airflow.utils.dates.days_ago(2), 'execID': _params['execID'], 'product': "LS8_OLI_LASRC" } dag = DAG(dag_id=args["execID"], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=20)) ndvi = dag_utils.queryMapByTile( lat=_params['lat'], lon=_params['lon'], product=_params['products'][0], time_ranges=_params['time_ranges'][0], algorithm=_steps['ndvi']['algorithm'], version=_steps['ndvi']['version'], params=_steps['ndvi']['params'], queue=_steps['ndvi']['queue'], delete_partial_results=_steps['ndvi']['del_prev_result'], dag=dag, task_id="ndvi", to_tiff=not (_params['genera_mosaico'] and queue_utils.get_tiles(_params['lat'], _params['lon']) > 1)) bosque = dag_utils.IdentityMap( ndvi, algorithm=_steps['bosque']['algorithm'], product=_params['products'][0], version=_steps['bosque']['version'], params=_steps['bosque']['params'], queue=_steps['bosque']['queue'], delete_partial_results=_steps['ndvi']['del_prev_result'],
'start_date': airflow.utils.dates.days_ago(2), 'execID': "ndvi_anomaly", 'product': "LS8_OLI_LASRC" } dag = DAG( dag_id=args["execID"], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) consulta_baseline=dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges= _params['time_ranges'][0], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={ 'normalized':_params['normalized'], 'bands':_params['bands'], 'minValid': _params['minValid'] },queue=_queues['mascara-landsat'],dag=dag, task_id="consulta_baseline_"+_params['products'][0] ) consulta_analysis=dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges= _params['time_ranges'][1], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={ 'normalized':_params['normalized'], 'bands':_params['bands'], 'minValid': _params['minValid'] },queue=_queues['mascara-landsat'],dag=dag, task_id="consulta_analysis_{}_".format(_params['products'][0])
'execID': "ndviMultiUnidad", 'product': "Multiple" } dag = DAG(dag_id='ndvi_multiunidad', default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) maskedLS8 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product="LS8_OLI_LASRC", params={ 'normalized': _params['normalized'], 'bands': _params['bands'], 'minValid': _params['minValid'], }, dag=dag, taxprefix="maskedLS8_") maskedLS7 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'], algorithm="mascara-landsat", version="1.0", product="LS7_ETM_LEDAPS", params={ 'normalized': _params['normalized'],
'panchromatic', 'cirrus', 'tirs1', 'tirs2') #Define las bandas que se especifican en el Json para la versión 7 de landsat. LS7_JsonBands = [val for val in data['Bands'] if val in LS7_bands] LS8_JsonBands = [val for val in data['Bands'] if val in LS8_bands] #Se genera la tarea maskedLS8 sólo si en el archivo Json especifican LS8 como el producto o uno de los productos if 'LS8' in data['Product']: maskedLS8 = dag_utils.queryMapByTile(lat=data['Lat'], lon=data['Lon'], time_ranges=[(data['Time_range'][0]), data['Time_range'][1]], algorithm="mascara-landsat", version="1.0", product=data['Product'], params={ 'normalized': data['Normalized'], 'bands': LS8_JsonBands, 'minValid': data['Min_valid'], }, dag=dag, taxprefix="maskedLS8_") if 'LS7' in data['Product']: maskedLS7 = dag_utils.queryMapByTile(lat=data['Lat'], lon=data['Lon'], time_ranges=[(data['Time_range'][0]), data['Time_range'][1]], algorithm="mascara-landsat", version="1.0", product=data['Product'],
'start_date': airflow.utils.dates.days_ago(2), 'execID': "deteccion_de_cambios_PCA", 'product': _params['products'][0] } dag = DAG(dag_id=args["execID"], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) period1 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][0], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={'bands': _params['bands']}, queue=_queues['mascara-landsat'], dag=dag, task_id="masked_p_1_" + _params['products'][0]) period2 = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][1], algorithm="mascara-landsat", version="1.0", product=_params['products'][0], params={'bands': _params['bands']}, queue=_queues['mascara-landsat'], dag=dag,
'owner': _params['owner'], 'start_date': airflow.utils.dates.days_ago(2), 'execID':_params['execID'], 'product': _params['products'][2] } dag = DAG( dag_id=args['execID'], default_args=args, schedule_interval=None, dagrun_timeout=timedelta(minutes=120)) mascara_ls7_mosaic = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=_params['time_ranges'][2], algorithm=_steps['mascara']['algorithm'], version=_steps['mascara']['version'], product=_params['products'][2], params=_steps['mascara']['params'], delete_partial_results=_steps['consulta']['del_prev_result'], queue=_steps['mascara']['queue'], dag=dag, task_id="consulta_cubo_" + _params['products'][2]['name']) mascara_dem_mosaic = dag_utils.queryMapByTile(lat=_params['lat'], lon=_params['lon'], time_ranges=('2013-01-01', '2013-12-31'), algorithm=_steps['consulta']['algorithm'], version=_steps['consulta']['version'], product=_params['products'][0], params=_steps['consulta']['params'], delete_partial_results=_steps['consulta']['del_prev_result'], queue=_steps['consulta']['queue'], dag=dag, task_id="consulta_referencia_" + _params['products'][0]['name'])