Merge rework of #128 and related tweaks

examples/gee_example.py

@@ -1,31 +1,26 @@
 import openeo
+from openeo.internal.graph_building import PGNode
 import logging
 import time
 import json
-from openeo.auth.auth_bearer import BearerAuth
-
 logging.basicConfig(level=logging.INFO)
 
-
-GEE_DRIVER_URL = "https://earthengine.openeo.org/v0.4"
+GEE_DRIVER_URL = "https://earthengine.openeo.org/v1.0"
 
 OUTPUT_FILE = "/tmp/openeo_gee_output.png"
 
 user = "group1"
 password = "test123"
 
-#connect with GEE backend
-#session = openeo.session("nobody", GEE_DRIVER_URL)
-
-#TODO update example
-con = openeo.connect(GEE_DRIVER_URL, auth_type=BearerAuth, auth_options={"username": user, "password": password})
+# Connect to backend via basic authentication
+con = openeo.connect(GEE_DRIVER_URL)
+con.authenticate_basic(user, password)
 
-#Test Connection
+# Get information about the backend
 print(con.list_processes())
 print(con.list_collections())
 print(con.describe_collection("COPERNICUS/S2"))
 
-
 # Test Capabilities
 cap = con.capabilities()
 
@@ -34,68 +29,33 @@
 print(cap.currency())
 print(cap.list_plans())
 
-# Test Processes
+datacube = con.load_collection("COPERNICUS/S2",
+                               spatial_extent={"west": 16.138916, "south": 48.138600, "east": 16.524124, "north": 48.320647, "crs": "EPSG:4326"},
+                               temporal_extent=["2017-01-01T00:00:00Z", "2017-01-31T23:59:59Z"],
+                               bands=["B4", "B8"])
+
+# Defining complex reducer
+red = PGNode("array_element", arguments={"data": {"from_parameter": "data"}, "label": "B4"})
+nir = PGNode("array_element", arguments={"data": {"from_parameter": "data"}, "label": "B8"})
+ndvi = PGNode("normalized_difference", arguments={"x": {"from_node": nir}, "y": {"from_node": red}})
+
+datacube = datacube.reduce_dimension(dimension="bands", reducer=ndvi)
 
-datacube = con.imagecollection("COPERNICUS/S2")
-datacube = datacube.filter_bbox(west=16.138916, south=48.138600, east=16.524124, north=48.320647, crs="EPSG:4326")
-datacube = datacube.filter_daterange(extent=["2017-01-01T00:00:00Z", "2017-01-31T23:59:59Z"])
-datacube = datacube.ndvi(nir="B4", red="B8A")
-datacube = datacube.min_time()
 print(json.dumps(datacube.graph, indent=2))
 
-# Test Job
-
-job = con.create_job(datacube.graph)
-print(job.job_id)
-print(job.start_job())
-print (job.describe_job())
-time.sleep(5)
-job.download_results("/tmp/testfile")
-
-
-
-# PoC JSON:
-# {
-#     "process_graph":{
-#         "process_id":"stretch_colors",
-#         "args":{
-#             "imagery":{
-#                 "process_id":"min_time",
-#                 "args":{
-#                     "imagery":{
-#                         "process_id":"NDVI",
-#                         "args":{
-#                             "imagery":{
-#                                 "process_id":"filter_daterange",
-#                                 "args":{
-#                                     "imagery":{
-#                                         "process_id":"filter_bbox",
-#                                         "args":{
-#                                             "imagery":{
-#                                                 "product_id":"COPERNICUS/S2"
-#                                             },
-#                                             "left":9.0,
-#                                             "right":9.1,
-#                                             "top":12.1,
-#                                             "bottom":12.0,
-#                                             "srs":"EPSG:4326"
-#                                         }
-#                                     },
-#                                     "from":"2017-01-01",
-#                                     "to":"2017-01-31"
-#                                 }
-#                             },
-#                             "red":"B4",
-#                             "nir":"B8"
-#                         }
-#                     }
-#                 }
-#             },
-#             "min": -1,
-#             "max": 1
-#         }
-#     },
-#     "output":{
-#         "format":"png"
-#     }
-# }
+datacube = datacube.min_time(dimension="t")
+
+# defining linear scale range for apply process
+lin_scale = PGNode("linear_scale_range", arguments={"x": {"from_parameter": "x"}, "inputMin": -1, "inputMax": 1, "outputMax": 255})
+
+datacube = datacube.apply(lin_scale)
+datacube = datacube.save_result(format="PNG")
+print(json.dumps(datacube.graph, indent=2))
+
+# Send Job to backend
+job = datacube.send_job()
+print(job.describe_job())
+
+# Wait for job to finish and download
+res = job.start_and_wait().download_results("/tmp")
+print(res)