parser.add_argument("--output",nargs="?",type=str,help="output type (print/JSON) "); parser.add_argument("--save_sum",action='store_true',help="If True, sum of potential output will be saved for all grid cells in outfile+_sum.npy. False by default. "); parser.set_defaults(save_sum=False) args = parser.parse_args(); server = args.server[0]; port = args.port username = args.username; password = args.password; cutoutname = args.cutoutname[0]; cutoutuser = args.cutoutuser conversion_name = args.name; save_sum = args.save_sum onshorecurve = reatlas_client.turbineconf_to_powercurve_object(args.onshorepowercurve[0]); offshorecurve = reatlas_client.turbineconf_to_powercurve_object(args.offshorepowercurve[0]); capacitylayouts = args.capacitylayout; output = args.output if (username == None): username = raw_input("username: "******"password: "); try: if (port != None): atlas = reatlas_client.REatlas(server,port); else: atlas = reatlas_client.REatlas(server);
print("56.9,7.5 degrees has index " + str((i, j)) + ".") # Prepare for wind conversion: # Make a capacity layout with 0 everywhere but in (i,j) layout = numpy.zeros(Denmark["latitudes"].shape) layout[i, j] = 1.0 # Upload it numpy.save("layout.npy", layout) atlas.upload_file(filename="layout.npy") # Load the power curve Vestas90 = reatlas_client.turbineconf_to_powercurve_object("TurbineConfig/Vestas_V90_3MW.cfg") # Start a wind conversion on Denmark: atlas.select_cutout(cutoutname="Denmark", username="******") wind_job = atlas.convert_and_aggregate_wind( result_name="myresult", onshorepowercurve=Vestas90, offshorepowercurve=Vestas90, capacitylayouts=["layout.npy"] ) # Find the temporal index for January 13, 1992 at 05.00 UTC idx = numpy.where(Denmark["dates"] == datetime.datetime(1992, 1, 13, 5, 0))[0][0] print("January 13, 1992 at 05.00 UTC has index " + str(idx) + ".")