'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'])
