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))
